Analysis of 111/999 NHS calls and 111 online reports
Quentin Leclerc, Emily Nightingale, Samuel Abbott & Thibaut Jombart, for CMMID
Friday 12 March 2021
1 Data preparation
1.1 Outline
Load scripts: loads libraries and useful scripts used in the analyses; all
.Rfiles contained inscriptsat the root of the factory are automatically loadedLoad data: imports datasets, and may contain some ad hoc changes to the data such as specific data cleaning (not used in other reports), new variables used in the analyses, etc.
1.2 Load packages
library(reportfactory)
library(here)
library(rio)
library(tidyverse)
library(incidence)
library(distcrete)
library(epitrix)
library(earlyR)
library(projections)
library(linelist)
library(remotes)
library(janitor)
library(kableExtra)
library(DT)
library(cyphr)
library(chngpt)
library(lubridate)
library(ggpubr)
library(ggnewscale)1.3 Load scripts
These scripts will load:
- all scripts stored as
.Rfiles inside/scripts/ - all scripts stored as
.Rfiles inside/src/
These scripts also contain routines to access the latest clean encrypted data (see next section).
1.4 Load clean data
We import the latest NHS pathways data:
x <- import_pathways() %>%
as_tibble()
x
## # A tibble: 462,409 x 11
## site_type date sex age ccg_code ccg_name count postcode nhs_region
## <chr> <date> <chr> <chr> <chr> <chr> <int> <chr> <chr>
## 1 111 2020-03-18 female miss… e380000… nhs_glo… 1 gl34fe South West
## 2 111 2020-03-18 female miss… e380001… nhs_sou… 1 ne325nn North Eas…
## 3 111 2020-03-18 female 0-18 e380000… nhs_air… 8 bd57jr North Eas…
## 4 111 2020-03-18 female 0-18 e380000… nhs_ash… 7 tn254ab South East
## 5 111 2020-03-18 female 0-18 e380000… nhs_bar… 35 rm13ae London
## 6 111 2020-03-18 female 0-18 e380000… nhs_bar… 9 n111np London
## 7 111 2020-03-18 female 0-18 e380000… nhs_bar… 11 s752py North Eas…
## 8 111 2020-03-18 female 0-18 e380000… nhs_bas… 19 ss143hg East of E…
## 9 111 2020-03-18 female 0-18 e380000… nhs_bas… 6 dn227xf North Eas…
## 10 111 2020-03-18 female 0-18 e380000… nhs_bat… 9 ba25rp South West
## # … with 462,399 more rows, and 2 more variables: day <int>, weekday <fct>We also import demographics data for NHS regions in England, used later in our analysis:
path <- here::here("data", "csv", "nhs_region_population_2018.csv")
nhs_region_pop <- rio::import(path) %>%
mutate(nhs_region = str_to_title(gsub("_"," ",nhs_region)))
nhs_region_pop$nhs_region <- gsub(" Of ", " of ", nhs_region_pop$nhs_region)
nhs_region_pop$nhs_region <- gsub(" And ", " and ", nhs_region_pop$nhs_region)
nhs_region_pop
## nhs_region variable value
## 1 North West 0-18 0.22538599
## 2 North East and Yorkshire 0-18 0.21876449
## 3 Midlands 0-18 0.22564656
## 4 East of England 0-18 0.22810783
## 5 London 0-18 0.23764782
## 6 South East 0-18 0.22458811
## 7 South West 0-18 0.20799797
## 8 North West 19-69 0.64274078
## 9 North East and Yorkshire 19-69 0.64437753
## 10 Midlands 19-69 0.63876675
## 11 East of England 19-69 0.63034229
## 12 London 19-69 0.67820084
## 13 South East 19-69 0.63267336
## 14 South West 19-69 0.63176131
## 15 North West 70-120 0.13187323
## 16 North East and Yorkshire 70-120 0.13685797
## 17 Midlands 70-120 0.13558669
## 18 East of England 70-120 0.14154988
## 19 London 70-120 0.08415135
## 20 South East 70-120 0.14273853
## 21 South West 70-120 0.16024072Finally, we import publically available deaths per NHS region:
dth <- import_deaths() %>%
mutate(nhs_region = str_to_title(gsub("_"," ",nhs_region)))
#truncation to account for reporting delay
delay_max <- 21
dth$nhs_region <- gsub(" Of ", " of ", dth$nhs_region)
dth$nhs_region <- gsub(" And ", " and ", dth$nhs_region)
dth
## date_report nhs_region deaths
## 1 2020-03-01 East of England 0
## 2 2020-03-02 East of England 1
## 3 2020-03-03 East of England 0
## 4 2020-03-04 East of England 0
## 5 2020-03-05 East of England 0
## 6 2020-03-06 East of England 1
## 7 2020-03-07 East of England 0
## 8 2020-03-08 East of England 0
## 9 2020-03-09 East of England 1
## 10 2020-03-10 East of England 0
## 11 2020-03-11 East of England 0
## 12 2020-03-12 East of England 0
## 13 2020-03-13 East of England 1
## 14 2020-03-14 East of England 2
## 15 2020-03-15 East of England 2
## 16 2020-03-16 East of England 1
## 17 2020-03-17 East of England 1
## 18 2020-03-18 East of England 5
## 19 2020-03-19 East of England 4
## 20 2020-03-20 East of England 2
## 21 2020-03-21 East of England 11
## 22 2020-03-22 East of England 12
## 23 2020-03-23 East of England 11
## 24 2020-03-24 East of England 19
## 25 2020-03-25 East of England 26
## 26 2020-03-26 East of England 36
## 27 2020-03-27 East of England 38
## 28 2020-03-28 East of England 28
## 29 2020-03-29 East of England 43
## 30 2020-03-30 East of England 45
## 31 2020-03-31 East of England 70
## 32 2020-04-01 East of England 63
## 33 2020-04-02 East of England 65
## 34 2020-04-03 East of England 80
## 35 2020-04-04 East of England 71
## 36 2020-04-05 East of England 76
## 37 2020-04-06 East of England 71
## 38 2020-04-07 East of England 93
## 39 2020-04-08 East of England 111
## 40 2020-04-09 East of England 87
## 41 2020-04-10 East of England 74
## 42 2020-04-11 East of England 92
## 43 2020-04-12 East of England 100
## 44 2020-04-13 East of England 78
## 45 2020-04-14 East of England 61
## 46 2020-04-15 East of England 82
## 47 2020-04-16 East of England 74
## 48 2020-04-17 East of England 86
## 49 2020-04-18 East of England 64
## 50 2020-04-19 East of England 67
## 51 2020-04-20 East of England 67
## 52 2020-04-21 East of England 75
## 53 2020-04-22 East of England 67
## 54 2020-04-23 East of England 49
## 55 2020-04-24 East of England 66
## 56 2020-04-25 East of England 54
## 57 2020-04-26 East of England 48
## 58 2020-04-27 East of England 46
## 59 2020-04-28 East of England 58
## 60 2020-04-29 East of England 32
## 61 2020-04-30 East of England 45
## 62 2020-05-01 East of England 49
## 63 2020-05-02 East of England 29
## 64 2020-05-03 East of England 41
## 65 2020-05-04 East of England 19
## 66 2020-05-05 East of England 36
## 67 2020-05-06 East of England 31
## 68 2020-05-07 East of England 33
## 69 2020-05-08 East of England 33
## 70 2020-05-09 East of England 29
## 71 2020-05-10 East of England 22
## 72 2020-05-11 East of England 18
## 73 2020-05-12 East of England 21
## 74 2020-05-13 East of England 27
## 75 2020-05-14 East of England 26
## 76 2020-05-15 East of England 19
## 77 2020-05-16 East of England 26
## 78 2020-05-17 East of England 17
## 79 2020-05-18 East of England 25
## 80 2020-05-19 East of England 15
## 81 2020-05-20 East of England 26
## 82 2020-05-21 East of England 21
## 83 2020-05-22 East of England 13
## 84 2020-05-23 East of England 12
## 85 2020-05-24 East of England 17
## 86 2020-05-25 East of England 25
## 87 2020-05-26 East of England 14
## 88 2020-05-27 East of England 12
## 89 2020-05-28 East of England 17
## 90 2020-05-29 East of England 16
## 91 2020-05-30 East of England 9
## 92 2020-05-31 East of England 8
## 93 2020-06-01 East of England 17
## 94 2020-06-02 East of England 14
## 95 2020-06-03 East of England 10
## 96 2020-06-04 East of England 7
## 97 2020-06-05 East of England 14
## 98 2020-06-06 East of England 5
## 99 2020-06-07 East of England 9
## 100 2020-06-08 East of England 7
## 101 2020-06-09 East of England 6
## 102 2020-06-10 East of England 8
## 103 2020-06-11 East of England 1
## 104 2020-06-12 East of England 9
## 105 2020-06-13 East of England 5
## 106 2020-06-14 East of England 4
## 107 2020-06-15 East of England 8
## 108 2020-06-16 East of England 3
## 109 2020-06-17 East of England 7
## 110 2020-06-18 East of England 4
## 111 2020-06-19 East of England 7
## 112 2020-06-20 East of England 4
## 113 2020-06-21 East of England 3
## 114 2020-06-22 East of England 6
## 115 2020-06-23 East of England 5
## 116 2020-06-24 East of England 4
## 117 2020-06-25 East of England 1
## 118 2020-06-26 East of England 5
## 119 2020-06-27 East of England 6
## 120 2020-06-28 East of England 8
## 121 2020-06-29 East of England 4
## 122 2020-06-30 East of England 5
## 123 2020-07-01 East of England 2
## 124 2020-07-02 East of England 5
## 125 2020-07-03 East of England 0
## 126 2020-07-04 East of England 3
## 127 2020-07-05 East of England 1
## 128 2020-07-06 East of England 2
## 129 2020-07-07 East of England 2
## 130 2020-07-08 East of England 0
## 131 2020-07-09 East of England 8
## 132 2020-07-10 East of England 4
## 133 2020-07-11 East of England 2
## 134 2020-07-12 East of England 1
## 135 2020-07-13 East of England 8
## 136 2020-07-14 East of England 2
## 137 2020-07-15 East of England 0
## 138 2020-07-16 East of England 0
## 139 2020-07-17 East of England 0
## 140 2020-07-18 East of England 0
## 141 2020-07-19 East of England 1
## 142 2020-07-20 East of England 1
## 143 2020-07-21 East of England 1
## 144 2020-07-22 East of England 2
## 145 2020-07-23 East of England 1
## 146 2020-07-24 East of England 1
## 147 2020-07-25 East of England 0
## 148 2020-07-26 East of England 1
## 149 2020-07-27 East of England 1
## 150 2020-07-28 East of England 2
## 151 2020-07-29 East of England 0
## 152 2020-07-30 East of England 0
## 153 2020-07-31 East of England 1
## 154 2020-08-01 East of England 0
## 155 2020-08-02 East of England 0
## 156 2020-08-03 East of England 0
## 157 2020-08-04 East of England 1
## 158 2020-08-05 East of England 1
## 159 2020-08-06 East of England 0
## 160 2020-08-07 East of England 1
## 161 2020-08-08 East of England 0
## 162 2020-08-09 East of England 0
## 163 2020-08-10 East of England 1
## 164 2020-08-11 East of England 2
## 165 2020-08-12 East of England 1
## 166 2020-08-13 East of England 0
## 167 2020-08-14 East of England 1
## 168 2020-08-15 East of England 1
## 169 2020-08-16 East of England 0
## 170 2020-08-17 East of England 0
## 171 2020-08-18 East of England 2
## 172 2020-08-19 East of England 1
## 173 2020-08-20 East of England 1
## 174 2020-08-21 East of England 0
## 175 2020-08-22 East of England 1
## 176 2020-08-23 East of England 1
## 177 2020-08-24 East of England 0
## 178 2020-08-25 East of England 0
## 179 2020-08-26 East of England 1
## 180 2020-08-27 East of England 1
## 181 2020-08-28 East of England 0
## 182 2020-08-29 East of England 0
## 183 2020-08-30 East of England 0
## 184 2020-08-31 East of England 0
## 185 2020-09-01 East of England 0
## 186 2020-09-02 East of England 0
## 187 2020-09-03 East of England 1
## 188 2020-09-04 East of England 1
## 189 2020-09-05 East of England 0
## 190 2020-09-06 East of England 1
## 191 2020-09-07 East of England 0
## 192 2020-09-08 East of England 0
## 193 2020-09-09 East of England 0
## 194 2020-09-10 East of England 0
## 195 2020-09-11 East of England 0
## 196 2020-09-12 East of England 0
## 197 2020-09-13 East of England 1
## 198 2020-09-14 East of England 1
## 199 2020-09-15 East of England 0
## 200 2020-09-16 East of England 0
## 201 2020-09-17 East of England 0
## 202 2020-09-18 East of England 0
## 203 2020-09-19 East of England 0
## 204 2020-09-20 East of England 2
## 205 2020-09-21 East of England 0
## 206 2020-09-22 East of England 2
## 207 2020-09-23 East of England 1
## 208 2020-09-24 East of England 0
## 209 2020-09-25 East of England 1
## 210 2020-09-26 East of England 1
## 211 2020-09-27 East of England 1
## 212 2020-09-28 East of England 2
## 213 2020-09-29 East of England 2
## 214 2020-09-30 East of England 2
## 215 2020-10-01 East of England 2
## 216 2020-10-02 East of England 1
## 217 2020-10-03 East of England 1
## 218 2020-10-04 East of England 0
## 219 2020-10-05 East of England 0
## 220 2020-10-06 East of England 4
## 221 2020-10-07 East of England 6
## 222 2020-10-08 East of England 3
## 223 2020-10-09 East of England 1
## 224 2020-10-10 East of England 6
## 225 2020-10-11 East of England 2
## 226 2020-10-12 East of England 2
## 227 2020-10-13 East of England 1
## 228 2020-10-14 East of England 3
## 229 2020-10-15 East of England 4
## 230 2020-10-16 East of England 5
## 231 2020-10-17 East of England 6
## 232 2020-10-18 East of England 7
## 233 2020-10-19 East of England 5
## 234 2020-10-20 East of England 9
## 235 2020-10-21 East of England 8
## 236 2020-10-22 East of England 7
## 237 2020-10-23 East of England 14
## 238 2020-10-24 East of England 1
## 239 2020-10-25 East of England 10
## 240 2020-10-26 East of England 10
## 241 2020-10-27 East of England 8
## 242 2020-10-28 East of England 12
## 243 2020-10-29 East of England 10
## 244 2020-10-30 East of England 12
## 245 2020-10-31 East of England 15
## 246 2020-11-01 East of England 14
## 247 2020-11-02 East of England 9
## 248 2020-11-03 East of England 14
## 249 2020-11-04 East of England 11
## 250 2020-11-05 East of England 12
## 251 2020-11-06 East of England 18
## 252 2020-11-07 East of England 10
## 253 2020-11-08 East of England 13
## 254 2020-11-09 East of England 16
## 255 2020-11-10 East of England 26
## 256 2020-11-11 East of England 14
## 257 2020-11-12 East of England 14
## 258 2020-11-13 East of England 21
## 259 2020-11-14 East of England 19
## 260 2020-11-15 East of England 13
## 261 2020-11-16 East of England 11
## 262 2020-11-17 East of England 17
## 263 2020-11-18 East of England 19
## 264 2020-11-19 East of England 23
## 265 2020-11-20 East of England 24
## 266 2020-11-21 East of England 19
## 267 2020-11-22 East of England 21
## 268 2020-11-23 East of England 18
## 269 2020-11-24 East of England 21
## 270 2020-11-25 East of England 19
## 271 2020-11-26 East of England 19
## 272 2020-11-27 East of England 14
## 273 2020-11-28 East of England 28
## 274 2020-11-29 East of England 19
## 275 2020-11-30 East of England 22
## 276 2020-12-01 East of England 26
## 277 2020-12-02 East of England 18
## 278 2020-12-03 East of England 24
## 279 2020-12-04 East of England 25
## 280 2020-12-05 East of England 25
## 281 2020-12-06 East of England 21
## 282 2020-12-07 East of England 16
## 283 2020-12-08 East of England 26
## 284 2020-12-09 East of England 20
## 285 2020-12-10 East of England 32
## 286 2020-12-11 East of England 32
## 287 2020-12-12 East of England 27
## 288 2020-12-13 East of England 25
## 289 2020-12-14 East of England 32
## 290 2020-12-15 East of England 35
## 291 2020-12-16 East of England 29
## 292 2020-12-17 East of England 42
## 293 2020-12-18 East of England 44
## 294 2020-12-19 East of England 54
## 295 2020-12-20 East of England 52
## 296 2020-12-21 East of England 66
## 297 2020-12-22 East of England 52
## 298 2020-12-23 East of England 62
## 299 2020-12-24 East of England 61
## 300 2020-12-25 East of England 58
## 301 2020-12-26 East of England 64
## 302 2020-12-27 East of England 54
## 303 2020-12-28 East of England 71
## 304 2020-12-29 East of England 54
## 305 2020-12-30 East of England 76
## 306 2020-12-31 East of England 82
## 307 2021-01-01 East of England 89
## 308 2021-01-02 East of England 66
## 309 2021-01-03 East of England 78
## 310 2021-01-04 East of England 88
## 311 2021-01-05 East of England 102
## 312 2021-01-06 East of England 100
## 313 2021-01-07 East of England 116
## 314 2021-01-08 East of England 96
## 315 2021-01-09 East of England 133
## 316 2021-01-10 East of England 125
## 317 2021-01-11 East of England 126
## 318 2021-01-12 East of England 131
## 319 2021-01-13 East of England 131
## 320 2021-01-14 East of England 126
## 321 2021-01-15 East of England 119
## 322 2021-01-16 East of England 131
## 323 2021-01-17 East of England 133
## 324 2021-01-18 East of England 120
## 325 2021-01-19 East of England 129
## 326 2021-01-20 East of England 147
## 327 2021-01-21 East of England 135
## 328 2021-01-22 East of England 123
## 329 2021-01-23 East of England 102
## 330 2021-01-24 East of England 101
## 331 2021-01-25 East of England 112
## 332 2021-01-26 East of England 89
## 333 2021-01-27 East of England 94
## 334 2021-01-28 East of England 110
## 335 2021-01-29 East of England 95
## 336 2021-01-30 East of England 85
## 337 2021-01-31 East of England 73
## 338 2021-02-01 East of England 67
## 339 2021-02-02 East of England 74
## 340 2021-02-03 East of England 82
## 341 2021-02-04 East of England 75
## 342 2021-02-05 East of England 66
## 343 2021-02-06 East of England 77
## 344 2021-02-07 East of England 62
## 345 2021-02-08 East of England 73
## 346 2021-02-09 East of England 62
## 347 2021-02-10 East of England 52
## 348 2021-02-11 East of England 52
## 349 2021-02-12 East of England 47
## 350 2021-02-13 East of England 47
## 351 2021-02-14 East of England 32
## 352 2021-02-15 East of England 48
## 353 2021-02-16 East of England 46
## 354 2021-02-17 East of England 46
## 355 2021-02-18 East of England 29
## 356 2021-02-19 East of England 28
## 357 2021-02-20 East of England 30
## 358 2021-02-21 East of England 24
## 359 2021-02-22 East of England 26
## 360 2021-02-23 East of England 27
## 361 2021-02-24 East of England 17
## 362 2021-02-25 East of England 23
## 363 2021-02-26 East of England 15
## 364 2021-02-27 East of England 23
## 365 2021-02-28 East of England 17
## 366 2021-03-01 East of England 18
## 367 2021-03-02 East of England 19
## 368 2021-03-03 East of England 12
## 369 2021-03-04 East of England 18
## 370 2021-03-05 East of England 12
## 371 2021-03-06 East of England 12
## 372 2021-03-07 East of England 14
## 373 2021-03-08 East of England 14
## 374 2021-03-09 East of England 11
## 375 2021-03-10 East of England 0
## 376 2020-03-01 London 0
## 377 2020-03-02 London 0
## 378 2020-03-03 London 0
## 379 2020-03-04 London 0
## 380 2020-03-05 London 0
## 381 2020-03-06 London 1
## 382 2020-03-07 London 0
## 383 2020-03-08 London 0
## 384 2020-03-09 London 1
## 385 2020-03-10 London 0
## 386 2020-03-11 London 5
## 387 2020-03-12 London 6
## 388 2020-03-13 London 10
## 389 2020-03-14 London 13
## 390 2020-03-15 London 9
## 391 2020-03-16 London 15
## 392 2020-03-17 London 23
## 393 2020-03-18 London 28
## 394 2020-03-19 London 25
## 395 2020-03-20 London 44
## 396 2020-03-21 London 49
## 397 2020-03-22 London 54
## 398 2020-03-23 London 63
## 399 2020-03-24 London 86
## 400 2020-03-25 London 112
## 401 2020-03-26 London 130
## 402 2020-03-27 London 130
## 403 2020-03-28 London 123
## 404 2020-03-29 London 145
## 405 2020-03-30 London 151
## 406 2020-03-31 London 183
## 407 2020-04-01 London 202
## 408 2020-04-02 London 191
## 409 2020-04-03 London 199
## 410 2020-04-04 London 231
## 411 2020-04-05 London 195
## 412 2020-04-06 London 198
## 413 2020-04-07 London 220
## 414 2020-04-08 London 239
## 415 2020-04-09 London 207
## 416 2020-04-10 London 171
## 417 2020-04-11 London 178
## 418 2020-04-12 London 159
## 419 2020-04-13 London 166
## 420 2020-04-14 London 143
## 421 2020-04-15 London 143
## 422 2020-04-16 London 140
## 423 2020-04-17 London 101
## 424 2020-04-18 London 101
## 425 2020-04-19 London 104
## 426 2020-04-20 London 96
## 427 2020-04-21 London 96
## 428 2020-04-22 London 109
## 429 2020-04-23 London 77
## 430 2020-04-24 London 71
## 431 2020-04-25 London 58
## 432 2020-04-26 London 53
## 433 2020-04-27 London 52
## 434 2020-04-28 London 44
## 435 2020-04-29 London 45
## 436 2020-04-30 London 40
## 437 2020-05-01 London 41
## 438 2020-05-02 London 41
## 439 2020-05-03 London 36
## 440 2020-05-04 London 30
## 441 2020-05-05 London 25
## 442 2020-05-06 London 37
## 443 2020-05-07 London 37
## 444 2020-05-08 London 31
## 445 2020-05-09 London 23
## 446 2020-05-10 London 26
## 447 2020-05-11 London 18
## 448 2020-05-12 London 18
## 449 2020-05-13 London 17
## 450 2020-05-14 London 20
## 451 2020-05-15 London 19
## 452 2020-05-16 London 14
## 453 2020-05-17 London 16
## 454 2020-05-18 London 11
## 455 2020-05-19 London 14
## 456 2020-05-20 London 19
## 457 2020-05-21 London 12
## 458 2020-05-22 London 10
## 459 2020-05-23 London 6
## 460 2020-05-24 London 7
## 461 2020-05-25 London 9
## 462 2020-05-26 London 14
## 463 2020-05-27 London 7
## 464 2020-05-28 London 8
## 465 2020-05-29 London 7
## 466 2020-05-30 London 12
## 467 2020-05-31 London 6
## 468 2020-06-01 London 10
## 469 2020-06-02 London 8
## 470 2020-06-03 London 6
## 471 2020-06-04 London 8
## 472 2020-06-05 London 4
## 473 2020-06-06 London 0
## 474 2020-06-07 London 5
## 475 2020-06-08 London 5
## 476 2020-06-09 London 5
## 477 2020-06-10 London 8
## 478 2020-06-11 London 5
## 479 2020-06-12 London 3
## 480 2020-06-13 London 3
## 481 2020-06-14 London 3
## 482 2020-06-15 London 1
## 483 2020-06-16 London 2
## 484 2020-06-17 London 1
## 485 2020-06-18 London 2
## 486 2020-06-19 London 5
## 487 2020-06-20 London 3
## 488 2020-06-21 London 4
## 489 2020-06-22 London 2
## 490 2020-06-23 London 1
## 491 2020-06-24 London 4
## 492 2020-06-25 London 3
## 493 2020-06-26 London 2
## 494 2020-06-27 London 1
## 495 2020-06-28 London 2
## 496 2020-06-29 London 2
## 497 2020-06-30 London 1
## 498 2020-07-01 London 3
## 499 2020-07-02 London 2
## 500 2020-07-03 London 2
## 501 2020-07-04 London 1
## 502 2020-07-05 London 3
## 503 2020-07-06 London 2
## 504 2020-07-07 London 1
## 505 2020-07-08 London 3
## 506 2020-07-09 London 4
## 507 2020-07-10 London 0
## 508 2020-07-11 London 1
## 509 2020-07-12 London 1
## 510 2020-07-13 London 1
## 511 2020-07-14 London 0
## 512 2020-07-15 London 2
## 513 2020-07-16 London 0
## 514 2020-07-17 London 0
## 515 2020-07-18 London 2
## 516 2020-07-19 London 0
## 517 2020-07-20 London 0
## 518 2020-07-21 London 1
## 519 2020-07-22 London 0
## 520 2020-07-23 London 2
## 521 2020-07-24 London 0
## 522 2020-07-25 London 1
## 523 2020-07-26 London 0
## 524 2020-07-27 London 1
## 525 2020-07-28 London 0
## 526 2020-07-29 London 0
## 527 2020-07-30 London 1
## 528 2020-07-31 London 0
## 529 2020-08-01 London 0
## 530 2020-08-02 London 3
## 531 2020-08-03 London 0
## 532 2020-08-04 London 0
## 533 2020-08-05 London 0
## 534 2020-08-06 London 1
## 535 2020-08-07 London 0
## 536 2020-08-08 London 0
## 537 2020-08-09 London 0
## 538 2020-08-10 London 0
## 539 2020-08-11 London 1
## 540 2020-08-12 London 0
## 541 2020-08-13 London 2
## 542 2020-08-14 London 0
## 543 2020-08-15 London 0
## 544 2020-08-16 London 0
## 545 2020-08-17 London 1
## 546 2020-08-18 London 1
## 547 2020-08-19 London 0
## 548 2020-08-20 London 1
## 549 2020-08-21 London 0
## 550 2020-08-22 London 0
## 551 2020-08-23 London 0
## 552 2020-08-24 London 1
## 553 2020-08-25 London 1
## 554 2020-08-26 London 0
## 555 2020-08-27 London 0
## 556 2020-08-28 London 0
## 557 2020-08-29 London 0
## 558 2020-08-30 London 0
## 559 2020-08-31 London 1
## 560 2020-09-01 London 0
## 561 2020-09-02 London 1
## 562 2020-09-03 London 1
## 563 2020-09-04 London 0
## 564 2020-09-05 London 0
## 565 2020-09-06 London 2
## 566 2020-09-07 London 0
## 567 2020-09-08 London 0
## 568 2020-09-09 London 0
## 569 2020-09-10 London 2
## 570 2020-09-11 London 1
## 571 2020-09-12 London 1
## 572 2020-09-13 London 0
## 573 2020-09-14 London 0
## 574 2020-09-15 London 1
## 575 2020-09-16 London 2
## 576 2020-09-17 London 2
## 577 2020-09-18 London 1
## 578 2020-09-19 London 3
## 579 2020-09-20 London 3
## 580 2020-09-21 London 2
## 581 2020-09-22 London 6
## 582 2020-09-23 London 4
## 583 2020-09-24 London 3
## 584 2020-09-25 London 1
## 585 2020-09-26 London 1
## 586 2020-09-27 London 1
## 587 2020-09-28 London 3
## 588 2020-09-29 London 7
## 589 2020-09-30 London 6
## 590 2020-10-01 London 4
## 591 2020-10-02 London 1
## 592 2020-10-03 London 3
## 593 2020-10-04 London 2
## 594 2020-10-05 London 7
## 595 2020-10-06 London 4
## 596 2020-10-07 London 6
## 597 2020-10-08 London 6
## 598 2020-10-09 London 7
## 599 2020-10-10 London 3
## 600 2020-10-11 London 5
## 601 2020-10-12 London 7
## 602 2020-10-13 London 4
## 603 2020-10-14 London 6
## 604 2020-10-15 London 13
## 605 2020-10-16 London 6
## 606 2020-10-17 London 2
## 607 2020-10-18 London 5
## 608 2020-10-19 London 11
## 609 2020-10-20 London 8
## 610 2020-10-21 London 14
## 611 2020-10-22 London 12
## 612 2020-10-23 London 7
## 613 2020-10-24 London 18
## 614 2020-10-25 London 10
## 615 2020-10-26 London 10
## 616 2020-10-27 London 12
## 617 2020-10-28 London 23
## 618 2020-10-29 London 14
## 619 2020-10-30 London 17
## 620 2020-10-31 London 7
## 621 2020-11-01 London 17
## 622 2020-11-02 London 16
## 623 2020-11-03 London 10
## 624 2020-11-04 London 18
## 625 2020-11-05 London 17
## 626 2020-11-06 London 12
## 627 2020-11-07 London 21
## 628 2020-11-08 London 15
## 629 2020-11-09 London 28
## 630 2020-11-10 London 14
## 631 2020-11-11 London 15
## 632 2020-11-12 London 16
## 633 2020-11-13 London 14
## 634 2020-11-14 London 21
## 635 2020-11-15 London 18
## 636 2020-11-16 London 29
## 637 2020-11-17 London 29
## 638 2020-11-18 London 23
## 639 2020-11-19 London 24
## 640 2020-11-20 London 20
## 641 2020-11-21 London 19
## 642 2020-11-22 London 29
## 643 2020-11-23 London 19
## 644 2020-11-24 London 27
## 645 2020-11-25 London 30
## 646 2020-11-26 London 25
## 647 2020-11-27 London 28
## 648 2020-11-28 London 23
## 649 2020-11-29 London 40
## 650 2020-11-30 London 19
## 651 2020-12-01 London 28
## 652 2020-12-02 London 30
## 653 2020-12-03 London 27
## 654 2020-12-04 London 30
## 655 2020-12-05 London 26
## 656 2020-12-06 London 25
## 657 2020-12-07 London 30
## 658 2020-12-08 London 35
## 659 2020-12-09 London 28
## 660 2020-12-10 London 31
## 661 2020-12-11 London 27
## 662 2020-12-12 London 33
## 663 2020-12-13 London 33
## 664 2020-12-14 London 39
## 665 2020-12-15 London 49
## 666 2020-12-16 London 37
## 667 2020-12-17 London 57
## 668 2020-12-18 London 43
## 669 2020-12-19 London 42
## 670 2020-12-20 London 54
## 671 2020-12-21 London 60
## 672 2020-12-22 London 59
## 673 2020-12-23 London 58
## 674 2020-12-24 London 65
## 675 2020-12-25 London 82
## 676 2020-12-26 London 82
## 677 2020-12-27 London 92
## 678 2020-12-28 London 89
## 679 2020-12-29 London 110
## 680 2020-12-30 London 100
## 681 2020-12-31 London 110
## 682 2021-01-01 London 114
## 683 2021-01-02 London 126
## 684 2021-01-03 London 107
## 685 2021-01-04 London 149
## 686 2021-01-05 London 147
## 687 2021-01-06 London 147
## 688 2021-01-07 London 159
## 689 2021-01-08 London 139
## 690 2021-01-09 London 148
## 691 2021-01-10 London 161
## 692 2021-01-11 London 162
## 693 2021-01-12 London 171
## 694 2021-01-13 London 167
## 695 2021-01-14 London 156
## 696 2021-01-15 London 146
## 697 2021-01-16 London 159
## 698 2021-01-17 London 170
## 699 2021-01-18 London 186
## 700 2021-01-19 London 181
## 701 2021-01-20 London 159
## 702 2021-01-21 London 180
## 703 2021-01-22 London 141
## 704 2021-01-23 London 140
## 705 2021-01-24 London 128
## 706 2021-01-25 London 126
## 707 2021-01-26 London 118
## 708 2021-01-27 London 112
## 709 2021-01-28 London 109
## 710 2021-01-29 London 94
## 711 2021-01-30 London 88
## 712 2021-01-31 London 89
## 713 2021-02-01 London 77
## 714 2021-02-02 London 99
## 715 2021-02-03 London 107
## 716 2021-02-04 London 63
## 717 2021-02-05 London 85
## 718 2021-02-06 London 61
## 719 2021-02-07 London 71
## 720 2021-02-08 London 66
## 721 2021-02-09 London 57
## 722 2021-02-10 London 70
## 723 2021-02-11 London 47
## 724 2021-02-12 London 51
## 725 2021-02-13 London 43
## 726 2021-02-14 London 42
## 727 2021-02-15 London 37
## 728 2021-02-16 London 49
## 729 2021-02-17 London 43
## 730 2021-02-18 London 42
## 731 2021-02-19 London 41
## 732 2021-02-20 London 28
## 733 2021-02-21 London 35
## 734 2021-02-22 London 31
## 735 2021-02-23 London 23
## 736 2021-02-24 London 25
## 737 2021-02-25 London 20
## 738 2021-02-26 London 23
## 739 2021-02-27 London 17
## 740 2021-02-28 London 13
## 741 2021-03-01 London 25
## 742 2021-03-02 London 21
## 743 2021-03-03 London 8
## 744 2021-03-04 London 12
## 745 2021-03-05 London 16
## 746 2021-03-06 London 15
## 747 2021-03-07 London 8
## 748 2021-03-08 London 8
## 749 2021-03-09 London 5
## 750 2021-03-10 London 2
## 751 2020-03-01 Midlands 0
## 752 2020-03-02 Midlands 0
## 753 2020-03-03 Midlands 1
## 754 2020-03-04 Midlands 0
## 755 2020-03-05 Midlands 0
## 756 2020-03-06 Midlands 0
## 757 2020-03-07 Midlands 0
## 758 2020-03-08 Midlands 2
## 759 2020-03-09 Midlands 1
## 760 2020-03-10 Midlands 0
## 761 2020-03-11 Midlands 2
## 762 2020-03-12 Midlands 6
## 763 2020-03-13 Midlands 5
## 764 2020-03-14 Midlands 4
## 765 2020-03-15 Midlands 5
## 766 2020-03-16 Midlands 11
## 767 2020-03-17 Midlands 8
## 768 2020-03-18 Midlands 13
## 769 2020-03-19 Midlands 8
## 770 2020-03-20 Midlands 28
## 771 2020-03-21 Midlands 13
## 772 2020-03-22 Midlands 31
## 773 2020-03-23 Midlands 33
## 774 2020-03-24 Midlands 41
## 775 2020-03-25 Midlands 48
## 776 2020-03-26 Midlands 64
## 777 2020-03-27 Midlands 72
## 778 2020-03-28 Midlands 89
## 779 2020-03-29 Midlands 92
## 780 2020-03-30 Midlands 90
## 781 2020-03-31 Midlands 123
## 782 2020-04-01 Midlands 140
## 783 2020-04-02 Midlands 142
## 784 2020-04-03 Midlands 124
## 785 2020-04-04 Midlands 151
## 786 2020-04-05 Midlands 164
## 787 2020-04-06 Midlands 140
## 788 2020-04-07 Midlands 123
## 789 2020-04-08 Midlands 186
## 790 2020-04-09 Midlands 140
## 791 2020-04-10 Midlands 127
## 792 2020-04-11 Midlands 142
## 793 2020-04-12 Midlands 139
## 794 2020-04-13 Midlands 121
## 795 2020-04-14 Midlands 116
## 796 2020-04-15 Midlands 147
## 797 2020-04-16 Midlands 102
## 798 2020-04-17 Midlands 118
## 799 2020-04-18 Midlands 115
## 800 2020-04-19 Midlands 93
## 801 2020-04-20 Midlands 107
## 802 2020-04-21 Midlands 87
## 803 2020-04-22 Midlands 78
## 804 2020-04-23 Midlands 103
## 805 2020-04-24 Midlands 79
## 806 2020-04-25 Midlands 72
## 807 2020-04-26 Midlands 81
## 808 2020-04-27 Midlands 74
## 809 2020-04-28 Midlands 68
## 810 2020-04-29 Midlands 53
## 811 2020-04-30 Midlands 56
## 812 2020-05-01 Midlands 65
## 813 2020-05-02 Midlands 51
## 814 2020-05-03 Midlands 52
## 815 2020-05-04 Midlands 61
## 816 2020-05-05 Midlands 59
## 817 2020-05-06 Midlands 59
## 818 2020-05-07 Midlands 48
## 819 2020-05-08 Midlands 34
## 820 2020-05-09 Midlands 37
## 821 2020-05-10 Midlands 42
## 822 2020-05-11 Midlands 33
## 823 2020-05-12 Midlands 45
## 824 2020-05-13 Midlands 40
## 825 2020-05-14 Midlands 39
## 826 2020-05-15 Midlands 40
## 827 2020-05-16 Midlands 34
## 828 2020-05-17 Midlands 31
## 829 2020-05-18 Midlands 36
## 830 2020-05-19 Midlands 35
## 831 2020-05-20 Midlands 36
## 832 2020-05-21 Midlands 32
## 833 2020-05-22 Midlands 27
## 834 2020-05-23 Midlands 34
## 835 2020-05-24 Midlands 20
## 836 2020-05-25 Midlands 26
## 837 2020-05-26 Midlands 33
## 838 2020-05-27 Midlands 29
## 839 2020-05-28 Midlands 28
## 840 2020-05-29 Midlands 20
## 841 2020-05-30 Midlands 21
## 842 2020-05-31 Midlands 22
## 843 2020-06-01 Midlands 20
## 844 2020-06-02 Midlands 22
## 845 2020-06-03 Midlands 24
## 846 2020-06-04 Midlands 16
## 847 2020-06-05 Midlands 21
## 848 2020-06-06 Midlands 20
## 849 2020-06-07 Midlands 17
## 850 2020-06-08 Midlands 16
## 851 2020-06-09 Midlands 18
## 852 2020-06-10 Midlands 15
## 853 2020-06-11 Midlands 13
## 854 2020-06-12 Midlands 12
## 855 2020-06-13 Midlands 6
## 856 2020-06-14 Midlands 18
## 857 2020-06-15 Midlands 12
## 858 2020-06-16 Midlands 15
## 859 2020-06-17 Midlands 11
## 860 2020-06-18 Midlands 15
## 861 2020-06-19 Midlands 10
## 862 2020-06-20 Midlands 15
## 863 2020-06-21 Midlands 14
## 864 2020-06-22 Midlands 14
## 865 2020-06-23 Midlands 16
## 866 2020-06-24 Midlands 15
## 867 2020-06-25 Midlands 19
## 868 2020-06-26 Midlands 5
## 869 2020-06-27 Midlands 5
## 870 2020-06-28 Midlands 7
## 871 2020-06-29 Midlands 6
## 872 2020-06-30 Midlands 6
## 873 2020-07-01 Midlands 7
## 874 2020-07-02 Midlands 10
## 875 2020-07-03 Midlands 3
## 876 2020-07-04 Midlands 4
## 877 2020-07-05 Midlands 6
## 878 2020-07-06 Midlands 5
## 879 2020-07-07 Midlands 3
## 880 2020-07-08 Midlands 5
## 881 2020-07-09 Midlands 9
## 882 2020-07-10 Midlands 3
## 883 2020-07-11 Midlands 0
## 884 2020-07-12 Midlands 5
## 885 2020-07-13 Midlands 1
## 886 2020-07-14 Midlands 1
## 887 2020-07-15 Midlands 6
## 888 2020-07-16 Midlands 2
## 889 2020-07-17 Midlands 3
## 890 2020-07-18 Midlands 3
## 891 2020-07-19 Midlands 3
## 892 2020-07-20 Midlands 3
## 893 2020-07-21 Midlands 1
## 894 2020-07-22 Midlands 2
## 895 2020-07-23 Midlands 6
## 896 2020-07-24 Midlands 1
## 897 2020-07-25 Midlands 4
## 898 2020-07-26 Midlands 4
## 899 2020-07-27 Midlands 5
## 900 2020-07-28 Midlands 1
## 901 2020-07-29 Midlands 1
## 902 2020-07-30 Midlands 1
## 903 2020-07-31 Midlands 2
## 904 2020-08-01 Midlands 0
## 905 2020-08-02 Midlands 1
## 906 2020-08-03 Midlands 2
## 907 2020-08-04 Midlands 1
## 908 2020-08-05 Midlands 1
## 909 2020-08-06 Midlands 0
## 910 2020-08-07 Midlands 3
## 911 2020-08-08 Midlands 2
## 912 2020-08-09 Midlands 0
## 913 2020-08-10 Midlands 0
## 914 2020-08-11 Midlands 2
## 915 2020-08-12 Midlands 0
## 916 2020-08-13 Midlands 0
## 917 2020-08-14 Midlands 0
## 918 2020-08-15 Midlands 1
## 919 2020-08-16 Midlands 0
## 920 2020-08-17 Midlands 0
## 921 2020-08-18 Midlands 0
## 922 2020-08-19 Midlands 0
## 923 2020-08-20 Midlands 0
## 924 2020-08-21 Midlands 1
## 925 2020-08-22 Midlands 0
## 926 2020-08-23 Midlands 0
## 927 2020-08-24 Midlands 0
## 928 2020-08-25 Midlands 2
## 929 2020-08-26 Midlands 3
## 930 2020-08-27 Midlands 2
## 931 2020-08-28 Midlands 1
## 932 2020-08-29 Midlands 0
## 933 2020-08-30 Midlands 2
## 934 2020-08-31 Midlands 1
## 935 2020-09-01 Midlands 0
## 936 2020-09-02 Midlands 2
## 937 2020-09-03 Midlands 0
## 938 2020-09-04 Midlands 0
## 939 2020-09-05 Midlands 0
## 940 2020-09-06 Midlands 1
## 941 2020-09-07 Midlands 1
## 942 2020-09-08 Midlands 3
## 943 2020-09-09 Midlands 0
## 944 2020-09-10 Midlands 1
## 945 2020-09-11 Midlands 1
## 946 2020-09-12 Midlands 2
## 947 2020-09-13 Midlands 4
## 948 2020-09-14 Midlands 1
## 949 2020-09-15 Midlands 2
## 950 2020-09-16 Midlands 3
## 951 2020-09-17 Midlands 2
## 952 2020-09-18 Midlands 5
## 953 2020-09-19 Midlands 2
## 954 2020-09-20 Midlands 7
## 955 2020-09-21 Midlands 3
## 956 2020-09-22 Midlands 4
## 957 2020-09-23 Midlands 10
## 958 2020-09-24 Midlands 7
## 959 2020-09-25 Midlands 4
## 960 2020-09-26 Midlands 5
## 961 2020-09-27 Midlands 9
## 962 2020-09-28 Midlands 6
## 963 2020-09-29 Midlands 4
## 964 2020-09-30 Midlands 5
## 965 2020-10-01 Midlands 8
## 966 2020-10-02 Midlands 7
## 967 2020-10-03 Midlands 6
## 968 2020-10-04 Midlands 7
## 969 2020-10-05 Midlands 6
## 970 2020-10-06 Midlands 5
## 971 2020-10-07 Midlands 9
## 972 2020-10-08 Midlands 8
## 973 2020-10-09 Midlands 7
## 974 2020-10-10 Midlands 2
## 975 2020-10-11 Midlands 15
## 976 2020-10-12 Midlands 7
## 977 2020-10-13 Midlands 16
## 978 2020-10-14 Midlands 12
## 979 2020-10-15 Midlands 11
## 980 2020-10-16 Midlands 18
## 981 2020-10-17 Midlands 25
## 982 2020-10-18 Midlands 11
## 983 2020-10-19 Midlands 14
## 984 2020-10-20 Midlands 19
## 985 2020-10-21 Midlands 15
## 986 2020-10-22 Midlands 34
## 987 2020-10-23 Midlands 32
## 988 2020-10-24 Midlands 24
## 989 2020-10-25 Midlands 30
## 990 2020-10-26 Midlands 33
## 991 2020-10-27 Midlands 38
## 992 2020-10-28 Midlands 30
## 993 2020-10-29 Midlands 42
## 994 2020-10-30 Midlands 42
## 995 2020-10-31 Midlands 50
## 996 2020-11-01 Midlands 44
## 997 2020-11-02 Midlands 58
## 998 2020-11-03 Midlands 37
## 999 2020-11-04 Midlands 67
## 1000 2020-11-05 Midlands 50
## 1001 2020-11-06 Midlands 43
## 1002 2020-11-07 Midlands 60
## 1003 2020-11-08 Midlands 55
## 1004 2020-11-09 Midlands 67
## 1005 2020-11-10 Midlands 68
## 1006 2020-11-11 Midlands 58
## 1007 2020-11-12 Midlands 64
## 1008 2020-11-13 Midlands 47
## 1009 2020-11-14 Midlands 66
## 1010 2020-11-15 Midlands 72
## 1011 2020-11-16 Midlands 66
## 1012 2020-11-17 Midlands 66
## 1013 2020-11-18 Midlands 83
## 1014 2020-11-19 Midlands 73
## 1015 2020-11-20 Midlands 87
## 1016 2020-11-21 Midlands 59
## 1017 2020-11-22 Midlands 84
## 1018 2020-11-23 Midlands 80
## 1019 2020-11-24 Midlands 73
## 1020 2020-11-25 Midlands 74
## 1021 2020-11-26 Midlands 77
## 1022 2020-11-27 Midlands 78
## 1023 2020-11-28 Midlands 80
## 1024 2020-11-29 Midlands 86
## 1025 2020-11-30 Midlands 79
## 1026 2020-12-01 Midlands 74
## 1027 2020-12-02 Midlands 64
## 1028 2020-12-03 Midlands 82
## 1029 2020-12-04 Midlands 67
## 1030 2020-12-05 Midlands 71
## 1031 2020-12-06 Midlands 75
## 1032 2020-12-07 Midlands 68
## 1033 2020-12-08 Midlands 66
## 1034 2020-12-09 Midlands 63
## 1035 2020-12-10 Midlands 75
## 1036 2020-12-11 Midlands 65
## 1037 2020-12-12 Midlands 81
## 1038 2020-12-13 Midlands 78
## 1039 2020-12-14 Midlands 77
## 1040 2020-12-15 Midlands 73
## 1041 2020-12-16 Midlands 74
## 1042 2020-12-17 Midlands 86
## 1043 2020-12-18 Midlands 81
## 1044 2020-12-19 Midlands 57
## 1045 2020-12-20 Midlands 67
## 1046 2020-12-21 Midlands 85
## 1047 2020-12-22 Midlands 74
## 1048 2020-12-23 Midlands 58
## 1049 2020-12-24 Midlands 68
## 1050 2020-12-25 Midlands 81
## 1051 2020-12-26 Midlands 74
## 1052 2020-12-27 Midlands 87
## 1053 2020-12-28 Midlands 64
## 1054 2020-12-29 Midlands 83
## 1055 2020-12-30 Midlands 100
## 1056 2020-12-31 Midlands 89
## 1057 2021-01-01 Midlands 77
## 1058 2021-01-02 Midlands 76
## 1059 2021-01-03 Midlands 71
## 1060 2021-01-04 Midlands 96
## 1061 2021-01-05 Midlands 106
## 1062 2021-01-06 Midlands 112
## 1063 2021-01-07 Midlands 106
## 1064 2021-01-08 Midlands 131
## 1065 2021-01-09 Midlands 141
## 1066 2021-01-10 Midlands 122
## 1067 2021-01-11 Midlands 146
## 1068 2021-01-12 Midlands 161
## 1069 2021-01-13 Midlands 141
## 1070 2021-01-14 Midlands 157
## 1071 2021-01-15 Midlands 131
## 1072 2021-01-16 Midlands 150
## 1073 2021-01-17 Midlands 158
## 1074 2021-01-18 Midlands 163
## 1075 2021-01-19 Midlands 157
## 1076 2021-01-20 Midlands 150
## 1077 2021-01-21 Midlands 158
## 1078 2021-01-22 Midlands 160
## 1079 2021-01-23 Midlands 142
## 1080 2021-01-24 Midlands 168
## 1081 2021-01-25 Midlands 155
## 1082 2021-01-26 Midlands 144
## 1083 2021-01-27 Midlands 138
## 1084 2021-01-28 Midlands 140
## 1085 2021-01-29 Midlands 150
## 1086 2021-01-30 Midlands 124
## 1087 2021-01-31 Midlands 111
## 1088 2021-02-01 Midlands 137
## 1089 2021-02-02 Midlands 131
## 1090 2021-02-03 Midlands 135
## 1091 2021-02-04 Midlands 111
## 1092 2021-02-05 Midlands 111
## 1093 2021-02-06 Midlands 93
## 1094 2021-02-07 Midlands 109
## 1095 2021-02-08 Midlands 99
## 1096 2021-02-09 Midlands 96
## 1097 2021-02-10 Midlands 93
## 1098 2021-02-11 Midlands 91
## 1099 2021-02-12 Midlands 88
## 1100 2021-02-13 Midlands 67
## 1101 2021-02-14 Midlands 82
## 1102 2021-02-15 Midlands 86
## 1103 2021-02-16 Midlands 77
## 1104 2021-02-17 Midlands 66
## 1105 2021-02-18 Midlands 67
## 1106 2021-02-19 Midlands 54
## 1107 2021-02-20 Midlands 67
## 1108 2021-02-21 Midlands 56
## 1109 2021-02-22 Midlands 53
## 1110 2021-02-23 Midlands 55
## 1111 2021-02-24 Midlands 50
## 1112 2021-02-25 Midlands 52
## 1113 2021-02-26 Midlands 42
## 1114 2021-02-27 Midlands 42
## 1115 2021-02-28 Midlands 45
## 1116 2021-03-01 Midlands 40
## 1117 2021-03-02 Midlands 29
## 1118 2021-03-03 Midlands 38
## 1119 2021-03-04 Midlands 31
## 1120 2021-03-05 Midlands 31
## 1121 2021-03-06 Midlands 20
## 1122 2021-03-07 Midlands 14
## 1123 2021-03-08 Midlands 28
## 1124 2021-03-09 Midlands 19
## 1125 2021-03-10 Midlands 1
## 1126 2020-03-01 North East and Yorkshire 0
## 1127 2020-03-02 North East and Yorkshire 0
## 1128 2020-03-03 North East and Yorkshire 0
## 1129 2020-03-04 North East and Yorkshire 0
## 1130 2020-03-05 North East and Yorkshire 0
## 1131 2020-03-06 North East and Yorkshire 0
## 1132 2020-03-07 North East and Yorkshire 0
## 1133 2020-03-08 North East and Yorkshire 0
## 1134 2020-03-09 North East and Yorkshire 0
## 1135 2020-03-10 North East and Yorkshire 0
## 1136 2020-03-11 North East and Yorkshire 0
## 1137 2020-03-12 North East and Yorkshire 0
## 1138 2020-03-13 North East and Yorkshire 0
## 1139 2020-03-14 North East and Yorkshire 0
## 1140 2020-03-15 North East and Yorkshire 2
## 1141 2020-03-16 North East and Yorkshire 3
## 1142 2020-03-17 North East and Yorkshire 1
## 1143 2020-03-18 North East and Yorkshire 2
## 1144 2020-03-19 North East and Yorkshire 6
## 1145 2020-03-20 North East and Yorkshire 5
## 1146 2020-03-21 North East and Yorkshire 6
## 1147 2020-03-22 North East and Yorkshire 7
## 1148 2020-03-23 North East and Yorkshire 9
## 1149 2020-03-24 North East and Yorkshire 8
## 1150 2020-03-25 North East and Yorkshire 18
## 1151 2020-03-26 North East and Yorkshire 21
## 1152 2020-03-27 North East and Yorkshire 28
## 1153 2020-03-28 North East and Yorkshire 35
## 1154 2020-03-29 North East and Yorkshire 38
## 1155 2020-03-30 North East and Yorkshire 64
## 1156 2020-03-31 North East and Yorkshire 60
## 1157 2020-04-01 North East and Yorkshire 67
## 1158 2020-04-02 North East and Yorkshire 75
## 1159 2020-04-03 North East and Yorkshire 100
## 1160 2020-04-04 North East and Yorkshire 105
## 1161 2020-04-05 North East and Yorkshire 92
## 1162 2020-04-06 North East and Yorkshire 96
## 1163 2020-04-07 North East and Yorkshire 102
## 1164 2020-04-08 North East and Yorkshire 107
## 1165 2020-04-09 North East and Yorkshire 111
## 1166 2020-04-10 North East and Yorkshire 117
## 1167 2020-04-11 North East and Yorkshire 98
## 1168 2020-04-12 North East and Yorkshire 84
## 1169 2020-04-13 North East and Yorkshire 94
## 1170 2020-04-14 North East and Yorkshire 107
## 1171 2020-04-15 North East and Yorkshire 96
## 1172 2020-04-16 North East and Yorkshire 103
## 1173 2020-04-17 North East and Yorkshire 88
## 1174 2020-04-18 North East and Yorkshire 95
## 1175 2020-04-19 North East and Yorkshire 88
## 1176 2020-04-20 North East and Yorkshire 100
## 1177 2020-04-21 North East and Yorkshire 76
## 1178 2020-04-22 North East and Yorkshire 84
## 1179 2020-04-23 North East and Yorkshire 63
## 1180 2020-04-24 North East and Yorkshire 72
## 1181 2020-04-25 North East and Yorkshire 69
## 1182 2020-04-26 North East and Yorkshire 65
## 1183 2020-04-27 North East and Yorkshire 65
## 1184 2020-04-28 North East and Yorkshire 57
## 1185 2020-04-29 North East and Yorkshire 69
## 1186 2020-04-30 North East and Yorkshire 57
## 1187 2020-05-01 North East and Yorkshire 64
## 1188 2020-05-02 North East and Yorkshire 48
## 1189 2020-05-03 North East and Yorkshire 40
## 1190 2020-05-04 North East and Yorkshire 49
## 1191 2020-05-05 North East and Yorkshire 40
## 1192 2020-05-06 North East and Yorkshire 51
## 1193 2020-05-07 North East and Yorkshire 45
## 1194 2020-05-08 North East and Yorkshire 42
## 1195 2020-05-09 North East and Yorkshire 44
## 1196 2020-05-10 North East and Yorkshire 40
## 1197 2020-05-11 North East and Yorkshire 29
## 1198 2020-05-12 North East and Yorkshire 27
## 1199 2020-05-13 North East and Yorkshire 28
## 1200 2020-05-14 North East and Yorkshire 31
## 1201 2020-05-15 North East and Yorkshire 32
## 1202 2020-05-16 North East and Yorkshire 35
## 1203 2020-05-17 North East and Yorkshire 26
## 1204 2020-05-18 North East and Yorkshire 30
## 1205 2020-05-19 North East and Yorkshire 27
## 1206 2020-05-20 North East and Yorkshire 22
## 1207 2020-05-21 North East and Yorkshire 33
## 1208 2020-05-22 North East and Yorkshire 22
## 1209 2020-05-23 North East and Yorkshire 18
## 1210 2020-05-24 North East and Yorkshire 26
## 1211 2020-05-25 North East and Yorkshire 21
## 1212 2020-05-26 North East and Yorkshire 21
## 1213 2020-05-27 North East and Yorkshire 23
## 1214 2020-05-28 North East and Yorkshire 21
## 1215 2020-05-29 North East and Yorkshire 25
## 1216 2020-05-30 North East and Yorkshire 20
## 1217 2020-05-31 North East and Yorkshire 20
## 1218 2020-06-01 North East and Yorkshire 17
## 1219 2020-06-02 North East and Yorkshire 23
## 1220 2020-06-03 North East and Yorkshire 24
## 1221 2020-06-04 North East and Yorkshire 17
## 1222 2020-06-05 North East and Yorkshire 18
## 1223 2020-06-06 North East and Yorkshire 21
## 1224 2020-06-07 North East and Yorkshire 14
## 1225 2020-06-08 North East and Yorkshire 11
## 1226 2020-06-09 North East and Yorkshire 12
## 1227 2020-06-10 North East and Yorkshire 19
## 1228 2020-06-11 North East and Yorkshire 7
## 1229 2020-06-12 North East and Yorkshire 9
## 1230 2020-06-13 North East and Yorkshire 10
## 1231 2020-06-14 North East and Yorkshire 11
## 1232 2020-06-15 North East and Yorkshire 9
## 1233 2020-06-16 North East and Yorkshire 10
## 1234 2020-06-17 North East and Yorkshire 9
## 1235 2020-06-18 North East and Yorkshire 11
## 1236 2020-06-19 North East and Yorkshire 6
## 1237 2020-06-20 North East and Yorkshire 5
## 1238 2020-06-21 North East and Yorkshire 4
## 1239 2020-06-22 North East and Yorkshire 7
## 1240 2020-06-23 North East and Yorkshire 8
## 1241 2020-06-24 North East and Yorkshire 10
## 1242 2020-06-25 North East and Yorkshire 4
## 1243 2020-06-26 North East and Yorkshire 8
## 1244 2020-06-27 North East and Yorkshire 4
## 1245 2020-06-28 North East and Yorkshire 5
## 1246 2020-06-29 North East and Yorkshire 2
## 1247 2020-06-30 North East and Yorkshire 7
## 1248 2020-07-01 North East and Yorkshire 1
## 1249 2020-07-02 North East and Yorkshire 5
## 1250 2020-07-03 North East and Yorkshire 4
## 1251 2020-07-04 North East and Yorkshire 4
## 1252 2020-07-05 North East and Yorkshire 3
## 1253 2020-07-06 North East and Yorkshire 2
## 1254 2020-07-07 North East and Yorkshire 3
## 1255 2020-07-08 North East and Yorkshire 3
## 1256 2020-07-09 North East and Yorkshire 0
## 1257 2020-07-10 North East and Yorkshire 3
## 1258 2020-07-11 North East and Yorkshire 1
## 1259 2020-07-12 North East and Yorkshire 4
## 1260 2020-07-13 North East and Yorkshire 1
## 1261 2020-07-14 North East and Yorkshire 1
## 1262 2020-07-15 North East and Yorkshire 2
## 1263 2020-07-16 North East and Yorkshire 3
## 1264 2020-07-17 North East and Yorkshire 1
## 1265 2020-07-18 North East and Yorkshire 2
## 1266 2020-07-19 North East and Yorkshire 2
## 1267 2020-07-20 North East and Yorkshire 1
## 1268 2020-07-21 North East and Yorkshire 1
## 1269 2020-07-22 North East and Yorkshire 6
## 1270 2020-07-23 North East and Yorkshire 0
## 1271 2020-07-24 North East and Yorkshire 1
## 1272 2020-07-25 North East and Yorkshire 5
## 1273 2020-07-26 North East and Yorkshire 1
## 1274 2020-07-27 North East and Yorkshire 0
## 1275 2020-07-28 North East and Yorkshire 2
## 1276 2020-07-29 North East and Yorkshire 1
## 1277 2020-07-30 North East and Yorkshire 0
## 1278 2020-07-31 North East and Yorkshire 1
## 1279 2020-08-01 North East and Yorkshire 3
## 1280 2020-08-02 North East and Yorkshire 2
## 1281 2020-08-03 North East and Yorkshire 1
## 1282 2020-08-04 North East and Yorkshire 3
## 1283 2020-08-05 North East and Yorkshire 1
## 1284 2020-08-06 North East and Yorkshire 4
## 1285 2020-08-07 North East and Yorkshire 0
## 1286 2020-08-08 North East and Yorkshire 2
## 1287 2020-08-09 North East and Yorkshire 3
## 1288 2020-08-10 North East and Yorkshire 3
## 1289 2020-08-11 North East and Yorkshire 2
## 1290 2020-08-12 North East and Yorkshire 2
## 1291 2020-08-13 North East and Yorkshire 0
## 1292 2020-08-14 North East and Yorkshire 1
## 1293 2020-08-15 North East and Yorkshire 1
## 1294 2020-08-16 North East and Yorkshire 0
## 1295 2020-08-17 North East and Yorkshire 6
## 1296 2020-08-18 North East and Yorkshire 1
## 1297 2020-08-19 North East and Yorkshire 0
## 1298 2020-08-20 North East and Yorkshire 0
## 1299 2020-08-21 North East and Yorkshire 1
## 1300 2020-08-22 North East and Yorkshire 1
## 1301 2020-08-23 North East and Yorkshire 3
## 1302 2020-08-24 North East and Yorkshire 0
## 1303 2020-08-25 North East and Yorkshire 2
## 1304 2020-08-26 North East and Yorkshire 2
## 1305 2020-08-27 North East and Yorkshire 1
## 1306 2020-08-28 North East and Yorkshire 0
## 1307 2020-08-29 North East and Yorkshire 1
## 1308 2020-08-30 North East and Yorkshire 0
## 1309 2020-08-31 North East and Yorkshire 0
## 1310 2020-09-01 North East and Yorkshire 2
## 1311 2020-09-02 North East and Yorkshire 3
## 1312 2020-09-03 North East and Yorkshire 1
## 1313 2020-09-04 North East and Yorkshire 1
## 1314 2020-09-05 North East and Yorkshire 2
## 1315 2020-09-06 North East and Yorkshire 1
## 1316 2020-09-07 North East and Yorkshire 0
## 1317 2020-09-08 North East and Yorkshire 1
## 1318 2020-09-09 North East and Yorkshire 2
## 1319 2020-09-10 North East and Yorkshire 0
## 1320 2020-09-11 North East and Yorkshire 3
## 1321 2020-09-12 North East and Yorkshire 1
## 1322 2020-09-13 North East and Yorkshire 3
## 1323 2020-09-14 North East and Yorkshire 4
## 1324 2020-09-15 North East and Yorkshire 3
## 1325 2020-09-16 North East and Yorkshire 3
## 1326 2020-09-17 North East and Yorkshire 5
## 1327 2020-09-18 North East and Yorkshire 6
## 1328 2020-09-19 North East and Yorkshire 2
## 1329 2020-09-20 North East and Yorkshire 9
## 1330 2020-09-21 North East and Yorkshire 7
## 1331 2020-09-22 North East and Yorkshire 5
## 1332 2020-09-23 North East and Yorkshire 6
## 1333 2020-09-24 North East and Yorkshire 3
## 1334 2020-09-25 North East and Yorkshire 5
## 1335 2020-09-26 North East and Yorkshire 7
## 1336 2020-09-27 North East and Yorkshire 10
## 1337 2020-09-28 North East and Yorkshire 6
## 1338 2020-09-29 North East and Yorkshire 7
## 1339 2020-09-30 North East and Yorkshire 7
## 1340 2020-10-01 North East and Yorkshire 8
## 1341 2020-10-02 North East and Yorkshire 16
## 1342 2020-10-03 North East and Yorkshire 12
## 1343 2020-10-04 North East and Yorkshire 13
## 1344 2020-10-05 North East and Yorkshire 10
## 1345 2020-10-06 North East and Yorkshire 15
## 1346 2020-10-07 North East and Yorkshire 13
## 1347 2020-10-08 North East and Yorkshire 16
## 1348 2020-10-09 North East and Yorkshire 10
## 1349 2020-10-10 North East and Yorkshire 16
## 1350 2020-10-11 North East and Yorkshire 16
## 1351 2020-10-12 North East and Yorkshire 15
## 1352 2020-10-13 North East and Yorkshire 21
## 1353 2020-10-14 North East and Yorkshire 20
## 1354 2020-10-15 North East and Yorkshire 23
## 1355 2020-10-16 North East and Yorkshire 24
## 1356 2020-10-17 North East and Yorkshire 34
## 1357 2020-10-18 North East and Yorkshire 22
## 1358 2020-10-19 North East and Yorkshire 34
## 1359 2020-10-20 North East and Yorkshire 37
## 1360 2020-10-21 North East and Yorkshire 43
## 1361 2020-10-22 North East and Yorkshire 33
## 1362 2020-10-23 North East and Yorkshire 31
## 1363 2020-10-24 North East and Yorkshire 34
## 1364 2020-10-25 North East and Yorkshire 35
## 1365 2020-10-26 North East and Yorkshire 46
## 1366 2020-10-27 North East and Yorkshire 45
## 1367 2020-10-28 North East and Yorkshire 39
## 1368 2020-10-29 North East and Yorkshire 51
## 1369 2020-10-30 North East and Yorkshire 48
## 1370 2020-10-31 North East and Yorkshire 58
## 1371 2020-11-01 North East and Yorkshire 48
## 1372 2020-11-02 North East and Yorkshire 50
## 1373 2020-11-03 North East and Yorkshire 48
## 1374 2020-11-04 North East and Yorkshire 57
## 1375 2020-11-05 North East and Yorkshire 57
## 1376 2020-11-06 North East and Yorkshire 57
## 1377 2020-11-07 North East and Yorkshire 75
## 1378 2020-11-08 North East and Yorkshire 62
## 1379 2020-11-09 North East and Yorkshire 87
## 1380 2020-11-10 North East and Yorkshire 65
## 1381 2020-11-11 North East and Yorkshire 59
## 1382 2020-11-12 North East and Yorkshire 77
## 1383 2020-11-13 North East and Yorkshire 78
## 1384 2020-11-14 North East and Yorkshire 72
## 1385 2020-11-15 North East and Yorkshire 77
## 1386 2020-11-16 North East and Yorkshire 52
## 1387 2020-11-17 North East and Yorkshire 68
## 1388 2020-11-18 North East and Yorkshire 81
## 1389 2020-11-19 North East and Yorkshire 72
## 1390 2020-11-20 North East and Yorkshire 75
## 1391 2020-11-21 North East and Yorkshire 54
## 1392 2020-11-22 North East and Yorkshire 80
## 1393 2020-11-23 North East and Yorkshire 84
## 1394 2020-11-24 North East and Yorkshire 81
## 1395 2020-11-25 North East and Yorkshire 70
## 1396 2020-11-26 North East and Yorkshire 64
## 1397 2020-11-27 North East and Yorkshire 62
## 1398 2020-11-28 North East and Yorkshire 77
## 1399 2020-11-29 North East and Yorkshire 61
## 1400 2020-11-30 North East and Yorkshire 56
## 1401 2020-12-01 North East and Yorkshire 44
## 1402 2020-12-02 North East and Yorkshire 59
## 1403 2020-12-03 North East and Yorkshire 71
## 1404 2020-12-04 North East and Yorkshire 65
## 1405 2020-12-05 North East and Yorkshire 48
## 1406 2020-12-06 North East and Yorkshire 65
## 1407 2020-12-07 North East and Yorkshire 49
## 1408 2020-12-08 North East and Yorkshire 54
## 1409 2020-12-09 North East and Yorkshire 49
## 1410 2020-12-10 North East and Yorkshire 56
## 1411 2020-12-11 North East and Yorkshire 56
## 1412 2020-12-12 North East and Yorkshire 55
## 1413 2020-12-13 North East and Yorkshire 51
## 1414 2020-12-14 North East and Yorkshire 49
## 1415 2020-12-15 North East and Yorkshire 55
## 1416 2020-12-16 North East and Yorkshire 40
## 1417 2020-12-17 North East and Yorkshire 49
## 1418 2020-12-18 North East and Yorkshire 58
## 1419 2020-12-19 North East and Yorkshire 49
## 1420 2020-12-20 North East and Yorkshire 52
## 1421 2020-12-21 North East and Yorkshire 35
## 1422 2020-12-22 North East and Yorkshire 57
## 1423 2020-12-23 North East and Yorkshire 60
## 1424 2020-12-24 North East and Yorkshire 50
## 1425 2020-12-25 North East and Yorkshire 57
## 1426 2020-12-26 North East and Yorkshire 67
## 1427 2020-12-27 North East and Yorkshire 73
## 1428 2020-12-28 North East and Yorkshire 64
## 1429 2020-12-29 North East and Yorkshire 58
## 1430 2020-12-30 North East and Yorkshire 41
## 1431 2020-12-31 North East and Yorkshire 51
## 1432 2021-01-01 North East and Yorkshire 70
## 1433 2021-01-02 North East and Yorkshire 58
## 1434 2021-01-03 North East and Yorkshire 48
## 1435 2021-01-04 North East and Yorkshire 63
## 1436 2021-01-05 North East and Yorkshire 64
## 1437 2021-01-06 North East and Yorkshire 61
## 1438 2021-01-07 North East and Yorkshire 72
## 1439 2021-01-08 North East and Yorkshire 67
## 1440 2021-01-09 North East and Yorkshire 58
## 1441 2021-01-10 North East and Yorkshire 80
## 1442 2021-01-11 North East and Yorkshire 82
## 1443 2021-01-12 North East and Yorkshire 69
## 1444 2021-01-13 North East and Yorkshire 77
## 1445 2021-01-14 North East and Yorkshire 70
## 1446 2021-01-15 North East and Yorkshire 97
## 1447 2021-01-16 North East and Yorkshire 99
## 1448 2021-01-17 North East and Yorkshire 75
## 1449 2021-01-18 North East and Yorkshire 82
## 1450 2021-01-19 North East and Yorkshire 104
## 1451 2021-01-20 North East and Yorkshire 92
## 1452 2021-01-21 North East and Yorkshire 87
## 1453 2021-01-22 North East and Yorkshire 80
## 1454 2021-01-23 North East and Yorkshire 68
## 1455 2021-01-24 North East and Yorkshire 62
## 1456 2021-01-25 North East and Yorkshire 79
## 1457 2021-01-26 North East and Yorkshire 73
## 1458 2021-01-27 North East and Yorkshire 70
## 1459 2021-01-28 North East and Yorkshire 72
## 1460 2021-01-29 North East and Yorkshire 84
## 1461 2021-01-30 North East and Yorkshire 76
## 1462 2021-01-31 North East and Yorkshire 81
## 1463 2021-02-01 North East and Yorkshire 79
## 1464 2021-02-02 North East and Yorkshire 69
## 1465 2021-02-03 North East and Yorkshire 81
## 1466 2021-02-04 North East and Yorkshire 68
## 1467 2021-02-05 North East and Yorkshire 80
## 1468 2021-02-06 North East and Yorkshire 52
## 1469 2021-02-07 North East and Yorkshire 57
## 1470 2021-02-08 North East and Yorkshire 51
## 1471 2021-02-09 North East and Yorkshire 52
## 1472 2021-02-10 North East and Yorkshire 62
## 1473 2021-02-11 North East and Yorkshire 64
## 1474 2021-02-12 North East and Yorkshire 59
## 1475 2021-02-13 North East and Yorkshire 53
## 1476 2021-02-14 North East and Yorkshire 59
## 1477 2021-02-15 North East and Yorkshire 58
## 1478 2021-02-16 North East and Yorkshire 46
## 1479 2021-02-17 North East and Yorkshire 47
## 1480 2021-02-18 North East and Yorkshire 44
## 1481 2021-02-19 North East and Yorkshire 42
## 1482 2021-02-20 North East and Yorkshire 37
## 1483 2021-02-21 North East and Yorkshire 39
## 1484 2021-02-22 North East and Yorkshire 20
## 1485 2021-02-23 North East and Yorkshire 36
## 1486 2021-02-24 North East and Yorkshire 31
## 1487 2021-02-25 North East and Yorkshire 27
## 1488 2021-02-26 North East and Yorkshire 25
## 1489 2021-02-27 North East and Yorkshire 32
## 1490 2021-02-28 North East and Yorkshire 28
## 1491 2021-03-01 North East and Yorkshire 19
## 1492 2021-03-02 North East and Yorkshire 16
## 1493 2021-03-03 North East and Yorkshire 27
## 1494 2021-03-04 North East and Yorkshire 16
## 1495 2021-03-05 North East and Yorkshire 27
## 1496 2021-03-06 North East and Yorkshire 21
## 1497 2021-03-07 North East and Yorkshire 19
## 1498 2021-03-08 North East and Yorkshire 20
## 1499 2021-03-09 North East and Yorkshire 16
## 1500 2021-03-10 North East and Yorkshire 4
## 1501 2020-03-01 North West 0
## 1502 2020-03-02 North West 0
## 1503 2020-03-03 North West 0
## 1504 2020-03-04 North West 0
## 1505 2020-03-05 North West 1
## 1506 2020-03-06 North West 0
## 1507 2020-03-07 North West 0
## 1508 2020-03-08 North West 1
## 1509 2020-03-09 North West 0
## 1510 2020-03-10 North West 0
## 1511 2020-03-11 North West 0
## 1512 2020-03-12 North West 2
## 1513 2020-03-13 North West 3
## 1514 2020-03-14 North West 1
## 1515 2020-03-15 North West 4
## 1516 2020-03-16 North West 2
## 1517 2020-03-17 North West 4
## 1518 2020-03-18 North West 6
## 1519 2020-03-19 North West 7
## 1520 2020-03-20 North West 10
## 1521 2020-03-21 North West 11
## 1522 2020-03-22 North West 13
## 1523 2020-03-23 North West 15
## 1524 2020-03-24 North West 21
## 1525 2020-03-25 North West 21
## 1526 2020-03-26 North West 29
## 1527 2020-03-27 North West 36
## 1528 2020-03-28 North West 28
## 1529 2020-03-29 North West 46
## 1530 2020-03-30 North West 67
## 1531 2020-03-31 North West 52
## 1532 2020-04-01 North West 86
## 1533 2020-04-02 North West 96
## 1534 2020-04-03 North West 95
## 1535 2020-04-04 North West 98
## 1536 2020-04-05 North West 102
## 1537 2020-04-06 North West 100
## 1538 2020-04-07 North West 136
## 1539 2020-04-08 North West 127
## 1540 2020-04-09 North West 119
## 1541 2020-04-10 North West 117
## 1542 2020-04-11 North West 138
## 1543 2020-04-12 North West 125
## 1544 2020-04-13 North West 130
## 1545 2020-04-14 North West 130
## 1546 2020-04-15 North West 114
## 1547 2020-04-16 North West 135
## 1548 2020-04-17 North West 98
## 1549 2020-04-18 North West 114
## 1550 2020-04-19 North West 71
## 1551 2020-04-20 North West 83
## 1552 2020-04-21 North West 76
## 1553 2020-04-22 North West 87
## 1554 2020-04-23 North West 85
## 1555 2020-04-24 North West 67
## 1556 2020-04-25 North West 67
## 1557 2020-04-26 North West 55
## 1558 2020-04-27 North West 54
## 1559 2020-04-28 North West 57
## 1560 2020-04-29 North West 64
## 1561 2020-04-30 North West 60
## 1562 2020-05-01 North West 45
## 1563 2020-05-02 North West 56
## 1564 2020-05-03 North West 55
## 1565 2020-05-04 North West 48
## 1566 2020-05-05 North West 49
## 1567 2020-05-06 North West 44
## 1568 2020-05-07 North West 50
## 1569 2020-05-08 North West 43
## 1570 2020-05-09 North West 31
## 1571 2020-05-10 North West 42
## 1572 2020-05-11 North West 35
## 1573 2020-05-12 North West 38
## 1574 2020-05-13 North West 25
## 1575 2020-05-14 North West 26
## 1576 2020-05-15 North West 33
## 1577 2020-05-16 North West 32
## 1578 2020-05-17 North West 24
## 1579 2020-05-18 North West 31
## 1580 2020-05-19 North West 35
## 1581 2020-05-20 North West 27
## 1582 2020-05-21 North West 28
## 1583 2020-05-22 North West 26
## 1584 2020-05-23 North West 31
## 1585 2020-05-24 North West 26
## 1586 2020-05-25 North West 31
## 1587 2020-05-26 North West 27
## 1588 2020-05-27 North West 27
## 1589 2020-05-28 North West 28
## 1590 2020-05-29 North West 20
## 1591 2020-05-30 North West 19
## 1592 2020-05-31 North West 13
## 1593 2020-06-01 North West 12
## 1594 2020-06-02 North West 27
## 1595 2020-06-03 North West 22
## 1596 2020-06-04 North West 22
## 1597 2020-06-05 North West 16
## 1598 2020-06-06 North West 26
## 1599 2020-06-07 North West 20
## 1600 2020-06-08 North West 23
## 1601 2020-06-09 North West 17
## 1602 2020-06-10 North West 16
## 1603 2020-06-11 North West 16
## 1604 2020-06-12 North West 11
## 1605 2020-06-13 North West 10
## 1606 2020-06-14 North West 15
## 1607 2020-06-15 North West 16
## 1608 2020-06-16 North West 16
## 1609 2020-06-17 North West 13
## 1610 2020-06-18 North West 14
## 1611 2020-06-19 North West 7
## 1612 2020-06-20 North West 11
## 1613 2020-06-21 North West 8
## 1614 2020-06-22 North West 11
## 1615 2020-06-23 North West 13
## 1616 2020-06-24 North West 13
## 1617 2020-06-25 North West 15
## 1618 2020-06-26 North West 6
## 1619 2020-06-27 North West 7
## 1620 2020-06-28 North West 9
## 1621 2020-06-29 North West 9
## 1622 2020-06-30 North West 7
## 1623 2020-07-01 North West 3
## 1624 2020-07-02 North West 6
## 1625 2020-07-03 North West 7
## 1626 2020-07-04 North West 4
## 1627 2020-07-05 North West 6
## 1628 2020-07-06 North West 9
## 1629 2020-07-07 North West 8
## 1630 2020-07-08 North West 5
## 1631 2020-07-09 North West 10
## 1632 2020-07-10 North West 2
## 1633 2020-07-11 North West 5
## 1634 2020-07-12 North West 0
## 1635 2020-07-13 North West 6
## 1636 2020-07-14 North West 4
## 1637 2020-07-15 North West 5
## 1638 2020-07-16 North West 2
## 1639 2020-07-17 North West 4
## 1640 2020-07-18 North West 5
## 1641 2020-07-19 North West 3
## 1642 2020-07-20 North West 0
## 1643 2020-07-21 North West 2
## 1644 2020-07-22 North West 3
## 1645 2020-07-23 North West 3
## 1646 2020-07-24 North West 1
## 1647 2020-07-25 North West 1
## 1648 2020-07-26 North West 3
## 1649 2020-07-27 North West 1
## 1650 2020-07-28 North West 1
## 1651 2020-07-29 North West 2
## 1652 2020-07-30 North West 2
## 1653 2020-07-31 North West 0
## 1654 2020-08-01 North West 2
## 1655 2020-08-02 North West 1
## 1656 2020-08-03 North West 8
## 1657 2020-08-04 North West 3
## 1658 2020-08-05 North West 2
## 1659 2020-08-06 North West 2
## 1660 2020-08-07 North West 2
## 1661 2020-08-08 North West 2
## 1662 2020-08-09 North West 3
## 1663 2020-08-10 North West 2
## 1664 2020-08-11 North West 3
## 1665 2020-08-12 North West 0
## 1666 2020-08-13 North West 2
## 1667 2020-08-14 North West 2
## 1668 2020-08-15 North West 6
## 1669 2020-08-16 North West 2
## 1670 2020-08-17 North West 1
## 1671 2020-08-18 North West 2
## 1672 2020-08-19 North West 1
## 1673 2020-08-20 North West 1
## 1674 2020-08-21 North West 4
## 1675 2020-08-22 North West 3
## 1676 2020-08-23 North West 5
## 1677 2020-08-24 North West 4
## 1678 2020-08-25 North West 3
## 1679 2020-08-26 North West 4
## 1680 2020-08-27 North West 1
## 1681 2020-08-28 North West 2
## 1682 2020-08-29 North West 0
## 1683 2020-08-30 North West 2
## 1684 2020-08-31 North West 3
## 1685 2020-09-01 North West 0
## 1686 2020-09-02 North West 2
## 1687 2020-09-03 North West 1
## 1688 2020-09-04 North West 3
## 1689 2020-09-05 North West 6
## 1690 2020-09-06 North West 1
## 1691 2020-09-07 North West 8
## 1692 2020-09-08 North West 6
## 1693 2020-09-09 North West 5
## 1694 2020-09-10 North West 5
## 1695 2020-09-11 North West 1
## 1696 2020-09-12 North West 4
## 1697 2020-09-13 North West 2
## 1698 2020-09-14 North West 4
## 1699 2020-09-15 North West 4
## 1700 2020-09-16 North West 6
## 1701 2020-09-17 North West 7
## 1702 2020-09-18 North West 6
## 1703 2020-09-19 North West 3
## 1704 2020-09-20 North West 2
## 1705 2020-09-21 North West 2
## 1706 2020-09-22 North West 9
## 1707 2020-09-23 North West 14
## 1708 2020-09-24 North West 10
## 1709 2020-09-25 North West 8
## 1710 2020-09-26 North West 14
## 1711 2020-09-27 North West 11
## 1712 2020-09-28 North West 15
## 1713 2020-09-29 North West 12
## 1714 2020-09-30 North West 17
## 1715 2020-10-01 North West 17
## 1716 2020-10-02 North West 20
## 1717 2020-10-03 North West 15
## 1718 2020-10-04 North West 15
## 1719 2020-10-05 North West 15
## 1720 2020-10-06 North West 20
## 1721 2020-10-07 North West 20
## 1722 2020-10-08 North West 22
## 1723 2020-10-09 North West 24
## 1724 2020-10-10 North West 31
## 1725 2020-10-11 North West 31
## 1726 2020-10-12 North West 35
## 1727 2020-10-13 North West 26
## 1728 2020-10-14 North West 35
## 1729 2020-10-15 North West 36
## 1730 2020-10-16 North West 34
## 1731 2020-10-17 North West 52
## 1732 2020-10-18 North West 40
## 1733 2020-10-19 North West 43
## 1734 2020-10-20 North West 48
## 1735 2020-10-21 North West 51
## 1736 2020-10-22 North West 49
## 1737 2020-10-23 North West 50
## 1738 2020-10-24 North West 51
## 1739 2020-10-25 North West 63
## 1740 2020-10-26 North West 53
## 1741 2020-10-27 North West 49
## 1742 2020-10-28 North West 57
## 1743 2020-10-29 North West 74
## 1744 2020-10-30 North West 73
## 1745 2020-10-31 North West 63
## 1746 2020-11-01 North West 76
## 1747 2020-11-02 North West 65
## 1748 2020-11-03 North West 77
## 1749 2020-11-04 North West 64
## 1750 2020-11-05 North West 67
## 1751 2020-11-06 North West 76
## 1752 2020-11-07 North West 79
## 1753 2020-11-08 North West 83
## 1754 2020-11-09 North West 82
## 1755 2020-11-10 North West 68
## 1756 2020-11-11 North West 62
## 1757 2020-11-12 North West 64
## 1758 2020-11-13 North West 81
## 1759 2020-11-14 North West 61
## 1760 2020-11-15 North West 75
## 1761 2020-11-16 North West 74
## 1762 2020-11-17 North West 73
## 1763 2020-11-18 North West 71
## 1764 2020-11-19 North West 67
## 1765 2020-11-20 North West 52
## 1766 2020-11-21 North West 68
## 1767 2020-11-22 North West 52
## 1768 2020-11-23 North West 54
## 1769 2020-11-24 North West 64
## 1770 2020-11-25 North West 65
## 1771 2020-11-26 North West 53
## 1772 2020-11-27 North West 51
## 1773 2020-11-28 North West 46
## 1774 2020-11-29 North West 54
## 1775 2020-11-30 North West 48
## 1776 2020-12-01 North West 53
## 1777 2020-12-02 North West 48
## 1778 2020-12-03 North West 47
## 1779 2020-12-04 North West 48
## 1780 2020-12-05 North West 37
## 1781 2020-12-06 North West 43
## 1782 2020-12-07 North West 50
## 1783 2020-12-08 North West 49
## 1784 2020-12-09 North West 48
## 1785 2020-12-10 North West 49
## 1786 2020-12-11 North West 41
## 1787 2020-12-12 North West 48
## 1788 2020-12-13 North West 42
## 1789 2020-12-14 North West 51
## 1790 2020-12-15 North West 34
## 1791 2020-12-16 North West 41
## 1792 2020-12-17 North West 26
## 1793 2020-12-18 North West 47
## 1794 2020-12-19 North West 45
## 1795 2020-12-20 North West 37
## 1796 2020-12-21 North West 51
## 1797 2020-12-22 North West 52
## 1798 2020-12-23 North West 50
## 1799 2020-12-24 North West 58
## 1800 2020-12-25 North West 52
## 1801 2020-12-26 North West 56
## 1802 2020-12-27 North West 50
## 1803 2020-12-28 North West 48
## 1804 2020-12-29 North West 49
## 1805 2020-12-30 North West 49
## 1806 2020-12-31 North West 62
## 1807 2021-01-01 North West 54
## 1808 2021-01-02 North West 55
## 1809 2021-01-03 North West 57
## 1810 2021-01-04 North West 51
## 1811 2021-01-05 North West 56
## 1812 2021-01-06 North West 69
## 1813 2021-01-07 North West 61
## 1814 2021-01-08 North West 65
## 1815 2021-01-09 North West 69
## 1816 2021-01-10 North West 66
## 1817 2021-01-11 North West 79
## 1818 2021-01-12 North West 66
## 1819 2021-01-13 North West 85
## 1820 2021-01-14 North West 92
## 1821 2021-01-15 North West 87
## 1822 2021-01-16 North West 83
## 1823 2021-01-17 North West 81
## 1824 2021-01-18 North West 92
## 1825 2021-01-19 North West 92
## 1826 2021-01-20 North West 89
## 1827 2021-01-21 North West 85
## 1828 2021-01-22 North West 110
## 1829 2021-01-23 North West 103
## 1830 2021-01-24 North West 95
## 1831 2021-01-25 North West 86
## 1832 2021-01-26 North West 102
## 1833 2021-01-27 North West 104
## 1834 2021-01-28 North West 102
## 1835 2021-01-29 North West 99
## 1836 2021-01-30 North West 77
## 1837 2021-01-31 North West 85
## 1838 2021-02-01 North West 96
## 1839 2021-02-02 North West 82
## 1840 2021-02-03 North West 71
## 1841 2021-02-04 North West 79
## 1842 2021-02-05 North West 67
## 1843 2021-02-06 North West 62
## 1844 2021-02-07 North West 53
## 1845 2021-02-08 North West 73
## 1846 2021-02-09 North West 69
## 1847 2021-02-10 North West 72
## 1848 2021-02-11 North West 67
## 1849 2021-02-12 North West 67
## 1850 2021-02-13 North West 62
## 1851 2021-02-14 North West 50
## 1852 2021-02-15 North West 56
## 1853 2021-02-16 North West 55
## 1854 2021-02-17 North West 55
## 1855 2021-02-18 North West 52
## 1856 2021-02-19 North West 40
## 1857 2021-02-20 North West 33
## 1858 2021-02-21 North West 36
## 1859 2021-02-22 North West 25
## 1860 2021-02-23 North West 35
## 1861 2021-02-24 North West 34
## 1862 2021-02-25 North West 22
## 1863 2021-02-26 North West 38
## 1864 2021-02-27 North West 25
## 1865 2021-02-28 North West 32
## 1866 2021-03-01 North West 31
## 1867 2021-03-02 North West 13
## 1868 2021-03-03 North West 20
## 1869 2021-03-04 North West 12
## 1870 2021-03-05 North West 25
## 1871 2021-03-06 North West 13
## 1872 2021-03-07 North West 21
## 1873 2021-03-08 North West 14
## 1874 2021-03-09 North West 10
## 1875 2021-03-10 North West 2
## 1876 2020-03-01 South East 0
## 1877 2020-03-02 South East 0
## 1878 2020-03-03 South East 1
## 1879 2020-03-04 South East 0
## 1880 2020-03-05 South East 1
## 1881 2020-03-06 South East 0
## 1882 2020-03-07 South East 0
## 1883 2020-03-08 South East 1
## 1884 2020-03-09 South East 1
## 1885 2020-03-10 South East 1
## 1886 2020-03-11 South East 1
## 1887 2020-03-12 South East 0
## 1888 2020-03-13 South East 1
## 1889 2020-03-14 South East 1
## 1890 2020-03-15 South East 5
## 1891 2020-03-16 South East 8
## 1892 2020-03-17 South East 7
## 1893 2020-03-18 South East 10
## 1894 2020-03-19 South East 9
## 1895 2020-03-20 South East 13
## 1896 2020-03-21 South East 7
## 1897 2020-03-22 South East 25
## 1898 2020-03-23 South East 20
## 1899 2020-03-24 South East 22
## 1900 2020-03-25 South East 29
## 1901 2020-03-26 South East 35
## 1902 2020-03-27 South East 36
## 1903 2020-03-28 South East 36
## 1904 2020-03-29 South East 55
## 1905 2020-03-30 South East 58
## 1906 2020-03-31 South East 65
## 1907 2020-04-01 South East 66
## 1908 2020-04-02 South East 55
## 1909 2020-04-03 South East 72
## 1910 2020-04-04 South East 80
## 1911 2020-04-05 South East 82
## 1912 2020-04-06 South East 88
## 1913 2020-04-07 South East 100
## 1914 2020-04-08 South East 83
## 1915 2020-04-09 South East 104
## 1916 2020-04-10 South East 88
## 1917 2020-04-11 South East 88
## 1918 2020-04-12 South East 88
## 1919 2020-04-13 South East 84
## 1920 2020-04-14 South East 65
## 1921 2020-04-15 South East 72
## 1922 2020-04-16 South East 56
## 1923 2020-04-17 South East 86
## 1924 2020-04-18 South East 57
## 1925 2020-04-19 South East 70
## 1926 2020-04-20 South East 87
## 1927 2020-04-21 South East 51
## 1928 2020-04-22 South East 54
## 1929 2020-04-23 South East 57
## 1930 2020-04-24 South East 64
## 1931 2020-04-25 South East 51
## 1932 2020-04-26 South East 51
## 1933 2020-04-27 South East 41
## 1934 2020-04-28 South East 40
## 1935 2020-04-29 South East 47
## 1936 2020-04-30 South East 29
## 1937 2020-05-01 South East 37
## 1938 2020-05-02 South East 36
## 1939 2020-05-03 South East 17
## 1940 2020-05-04 South East 35
## 1941 2020-05-05 South East 29
## 1942 2020-05-06 South East 25
## 1943 2020-05-07 South East 27
## 1944 2020-05-08 South East 26
## 1945 2020-05-09 South East 28
## 1946 2020-05-10 South East 19
## 1947 2020-05-11 South East 25
## 1948 2020-05-12 South East 27
## 1949 2020-05-13 South East 18
## 1950 2020-05-14 South East 32
## 1951 2020-05-15 South East 25
## 1952 2020-05-16 South East 22
## 1953 2020-05-17 South East 18
## 1954 2020-05-18 South East 23
## 1955 2020-05-19 South East 12
## 1956 2020-05-20 South East 22
## 1957 2020-05-21 South East 15
## 1958 2020-05-22 South East 17
## 1959 2020-05-23 South East 21
## 1960 2020-05-24 South East 17
## 1961 2020-05-25 South East 13
## 1962 2020-05-26 South East 19
## 1963 2020-05-27 South East 19
## 1964 2020-05-28 South East 12
## 1965 2020-05-29 South East 22
## 1966 2020-05-30 South East 8
## 1967 2020-05-31 South East 12
## 1968 2020-06-01 South East 11
## 1969 2020-06-02 South East 13
## 1970 2020-06-03 South East 18
## 1971 2020-06-04 South East 11
## 1972 2020-06-05 South East 11
## 1973 2020-06-06 South East 10
## 1974 2020-06-07 South East 12
## 1975 2020-06-08 South East 8
## 1976 2020-06-09 South East 11
## 1977 2020-06-10 South East 11
## 1978 2020-06-11 South East 5
## 1979 2020-06-12 South East 6
## 1980 2020-06-13 South East 7
## 1981 2020-06-14 South East 7
## 1982 2020-06-15 South East 8
## 1983 2020-06-16 South East 14
## 1984 2020-06-17 South East 10
## 1985 2020-06-18 South East 4
## 1986 2020-06-19 South East 7
## 1987 2020-06-20 South East 5
## 1988 2020-06-21 South East 3
## 1989 2020-06-22 South East 2
## 1990 2020-06-23 South East 9
## 1991 2020-06-24 South East 7
## 1992 2020-06-25 South East 5
## 1993 2020-06-26 South East 8
## 1994 2020-06-27 South East 9
## 1995 2020-06-28 South East 6
## 1996 2020-06-29 South East 5
## 1997 2020-06-30 South East 5
## 1998 2020-07-01 South East 2
## 1999 2020-07-02 South East 8
## 2000 2020-07-03 South East 3
## 2001 2020-07-04 South East 6
## 2002 2020-07-05 South East 5
## 2003 2020-07-06 South East 4
## 2004 2020-07-07 South East 6
## 2005 2020-07-08 South East 3
## 2006 2020-07-09 South East 7
## 2007 2020-07-10 South East 3
## 2008 2020-07-11 South East 4
## 2009 2020-07-12 South East 5
## 2010 2020-07-13 South East 5
## 2011 2020-07-14 South East 5
## 2012 2020-07-15 South East 6
## 2013 2020-07-16 South East 3
## 2014 2020-07-17 South East 1
## 2015 2020-07-18 South East 5
## 2016 2020-07-19 South East 2
## 2017 2020-07-20 South East 6
## 2018 2020-07-21 South East 4
## 2019 2020-07-22 South East 2
## 2020 2020-07-23 South East 3
## 2021 2020-07-24 South East 1
## 2022 2020-07-25 South East 1
## 2023 2020-07-26 South East 3
## 2024 2020-07-27 South East 1
## 2025 2020-07-28 South East 3
## 2026 2020-07-29 South East 2
## 2027 2020-07-30 South East 3
## 2028 2020-07-31 South East 1
## 2029 2020-08-01 South East 2
## 2030 2020-08-02 South East 4
## 2031 2020-08-03 South East 0
## 2032 2020-08-04 South East 0
## 2033 2020-08-05 South East 0
## 2034 2020-08-06 South East 2
## 2035 2020-08-07 South East 0
## 2036 2020-08-08 South East 2
## 2037 2020-08-09 South East 0
## 2038 2020-08-10 South East 2
## 2039 2020-08-11 South East 1
## 2040 2020-08-12 South East 1
## 2041 2020-08-13 South East 0
## 2042 2020-08-14 South East 0
## 2043 2020-08-15 South East 2
## 2044 2020-08-16 South East 1
## 2045 2020-08-17 South East 0
## 2046 2020-08-18 South East 2
## 2047 2020-08-19 South East 1
## 2048 2020-08-20 South East 0
## 2049 2020-08-21 South East 0
## 2050 2020-08-22 South East 0
## 2051 2020-08-23 South East 1
## 2052 2020-08-24 South East 0
## 2053 2020-08-25 South East 1
## 2054 2020-08-26 South East 0
## 2055 2020-08-27 South East 1
## 2056 2020-08-28 South East 2
## 2057 2020-08-29 South East 1
## 2058 2020-08-30 South East 0
## 2059 2020-08-31 South East 2
## 2060 2020-09-01 South East 1
## 2061 2020-09-02 South East 1
## 2062 2020-09-03 South East 0
## 2063 2020-09-04 South East 1
## 2064 2020-09-05 South East 0
## 2065 2020-09-06 South East 1
## 2066 2020-09-07 South East 0
## 2067 2020-09-08 South East 0
## 2068 2020-09-09 South East 0
## 2069 2020-09-10 South East 1
## 2070 2020-09-11 South East 1
## 2071 2020-09-12 South East 0
## 2072 2020-09-13 South East 3
## 2073 2020-09-14 South East 1
## 2074 2020-09-15 South East 2
## 2075 2020-09-16 South East 2
## 2076 2020-09-17 South East 3
## 2077 2020-09-18 South East 1
## 2078 2020-09-19 South East 1
## 2079 2020-09-20 South East 0
## 2080 2020-09-21 South East 3
## 2081 2020-09-22 South East 0
## 2082 2020-09-23 South East 2
## 2083 2020-09-24 South East 1
## 2084 2020-09-25 South East 3
## 2085 2020-09-26 South East 2
## 2086 2020-09-27 South East 2
## 2087 2020-09-28 South East 6
## 2088 2020-09-29 South East 3
## 2089 2020-09-30 South East 4
## 2090 2020-10-01 South East 4
## 2091 2020-10-02 South East 2
## 2092 2020-10-03 South East 1
## 2093 2020-10-04 South East 1
## 2094 2020-10-05 South East 2
## 2095 2020-10-06 South East 1
## 2096 2020-10-07 South East 4
## 2097 2020-10-08 South East 1
## 2098 2020-10-09 South East 1
## 2099 2020-10-10 South East 3
## 2100 2020-10-11 South East 3
## 2101 2020-10-12 South East 4
## 2102 2020-10-13 South East 2
## 2103 2020-10-14 South East 2
## 2104 2020-10-15 South East 3
## 2105 2020-10-16 South East 2
## 2106 2020-10-17 South East 3
## 2107 2020-10-18 South East 4
## 2108 2020-10-19 South East 7
## 2109 2020-10-20 South East 8
## 2110 2020-10-21 South East 9
## 2111 2020-10-22 South East 5
## 2112 2020-10-23 South East 7
## 2113 2020-10-24 South East 5
## 2114 2020-10-25 South East 9
## 2115 2020-10-26 South East 13
## 2116 2020-10-27 South East 10
## 2117 2020-10-28 South East 10
## 2118 2020-10-29 South East 7
## 2119 2020-10-30 South East 6
## 2120 2020-10-31 South East 15
## 2121 2020-11-01 South East 18
## 2122 2020-11-02 South East 13
## 2123 2020-11-03 South East 16
## 2124 2020-11-04 South East 10
## 2125 2020-11-05 South East 10
## 2126 2020-11-06 South East 16
## 2127 2020-11-07 South East 17
## 2128 2020-11-08 South East 18
## 2129 2020-11-09 South East 19
## 2130 2020-11-10 South East 20
## 2131 2020-11-11 South East 20
## 2132 2020-11-12 South East 20
## 2133 2020-11-13 South East 12
## 2134 2020-11-14 South East 24
## 2135 2020-11-15 South East 25
## 2136 2020-11-16 South East 22
## 2137 2020-11-17 South East 23
## 2138 2020-11-18 South East 26
## 2139 2020-11-19 South East 21
## 2140 2020-11-20 South East 18
## 2141 2020-11-21 South East 23
## 2142 2020-11-22 South East 30
## 2143 2020-11-23 South East 29
## 2144 2020-11-24 South East 26
## 2145 2020-11-25 South East 42
## 2146 2020-11-26 South East 30
## 2147 2020-11-27 South East 31
## 2148 2020-11-28 South East 24
## 2149 2020-11-29 South East 37
## 2150 2020-11-30 South East 23
## 2151 2020-12-01 South East 29
## 2152 2020-12-02 South East 33
## 2153 2020-12-03 South East 36
## 2154 2020-12-04 South East 41
## 2155 2020-12-05 South East 37
## 2156 2020-12-06 South East 32
## 2157 2020-12-07 South East 25
## 2158 2020-12-08 South East 43
## 2159 2020-12-09 South East 44
## 2160 2020-12-10 South East 38
## 2161 2020-12-11 South East 49
## 2162 2020-12-12 South East 40
## 2163 2020-12-13 South East 41
## 2164 2020-12-14 South East 38
## 2165 2020-12-15 South East 51
## 2166 2020-12-16 South East 45
## 2167 2020-12-17 South East 54
## 2168 2020-12-18 South East 48
## 2169 2020-12-19 South East 43
## 2170 2020-12-20 South East 57
## 2171 2020-12-21 South East 66
## 2172 2020-12-22 South East 62
## 2173 2020-12-23 South East 70
## 2174 2020-12-24 South East 56
## 2175 2020-12-25 South East 71
## 2176 2020-12-26 South East 75
## 2177 2020-12-27 South East 77
## 2178 2020-12-28 South East 81
## 2179 2020-12-29 South East 78
## 2180 2020-12-30 South East 92
## 2181 2020-12-31 South East 93
## 2182 2021-01-01 South East 60
## 2183 2021-01-02 South East 95
## 2184 2021-01-03 South East 79
## 2185 2021-01-04 South East 106
## 2186 2021-01-05 South East 107
## 2187 2021-01-06 South East 121
## 2188 2021-01-07 South East 116
## 2189 2021-01-08 South East 125
## 2190 2021-01-09 South East 115
## 2191 2021-01-10 South East 126
## 2192 2021-01-11 South East 128
## 2193 2021-01-12 South East 170
## 2194 2021-01-13 South East 134
## 2195 2021-01-14 South East 141
## 2196 2021-01-15 South East 126
## 2197 2021-01-16 South East 154
## 2198 2021-01-17 South East 165
## 2199 2021-01-18 South East 151
## 2200 2021-01-19 South East 154
## 2201 2021-01-20 South East 134
## 2202 2021-01-21 South East 133
## 2203 2021-01-22 South East 131
## 2204 2021-01-23 South East 122
## 2205 2021-01-24 South East 116
## 2206 2021-01-25 South East 114
## 2207 2021-01-26 South East 130
## 2208 2021-01-27 South East 113
## 2209 2021-01-28 South East 128
## 2210 2021-01-29 South East 109
## 2211 2021-01-30 South East 94
## 2212 2021-01-31 South East 94
## 2213 2021-02-01 South East 95
## 2214 2021-02-02 South East 83
## 2215 2021-02-03 South East 95
## 2216 2021-02-04 South East 58
## 2217 2021-02-05 South East 68
## 2218 2021-02-06 South East 73
## 2219 2021-02-07 South East 63
## 2220 2021-02-08 South East 67
## 2221 2021-02-09 South East 37
## 2222 2021-02-10 South East 46
## 2223 2021-02-11 South East 65
## 2224 2021-02-12 South East 43
## 2225 2021-02-13 South East 35
## 2226 2021-02-14 South East 43
## 2227 2021-02-15 South East 49
## 2228 2021-02-16 South East 38
## 2229 2021-02-17 South East 35
## 2230 2021-02-18 South East 40
## 2231 2021-02-19 South East 39
## 2232 2021-02-20 South East 32
## 2233 2021-02-21 South East 35
## 2234 2021-02-22 South East 31
## 2235 2021-02-23 South East 29
## 2236 2021-02-24 South East 27
## 2237 2021-02-25 South East 26
## 2238 2021-02-26 South East 21
## 2239 2021-02-27 South East 24
## 2240 2021-02-28 South East 14
## 2241 2021-03-01 South East 21
## 2242 2021-03-02 South East 20
## 2243 2021-03-03 South East 16
## 2244 2021-03-04 South East 24
## 2245 2021-03-05 South East 17
## 2246 2021-03-06 South East 11
## 2247 2021-03-07 South East 8
## 2248 2021-03-08 South East 9
## 2249 2021-03-09 South East 8
## 2250 2021-03-10 South East 2
## 2251 2020-03-01 South West 0
## 2252 2020-03-02 South West 0
## 2253 2020-03-03 South West 0
## 2254 2020-03-04 South West 0
## 2255 2020-03-05 South West 0
## 2256 2020-03-06 South West 0
## 2257 2020-03-07 South West 0
## 2258 2020-03-08 South West 0
## 2259 2020-03-09 South West 0
## 2260 2020-03-10 South West 0
## 2261 2020-03-11 South West 1
## 2262 2020-03-12 South West 0
## 2263 2020-03-13 South West 0
## 2264 2020-03-14 South West 1
## 2265 2020-03-15 South West 0
## 2266 2020-03-16 South West 0
## 2267 2020-03-17 South West 2
## 2268 2020-03-18 South West 2
## 2269 2020-03-19 South West 4
## 2270 2020-03-20 South West 3
## 2271 2020-03-21 South West 6
## 2272 2020-03-22 South West 7
## 2273 2020-03-23 South West 8
## 2274 2020-03-24 South West 7
## 2275 2020-03-25 South West 9
## 2276 2020-03-26 South West 11
## 2277 2020-03-27 South West 13
## 2278 2020-03-28 South West 21
## 2279 2020-03-29 South West 18
## 2280 2020-03-30 South West 23
## 2281 2020-03-31 South West 23
## 2282 2020-04-01 South West 21
## 2283 2020-04-02 South West 23
## 2284 2020-04-03 South West 30
## 2285 2020-04-04 South West 42
## 2286 2020-04-05 South West 32
## 2287 2020-04-06 South West 34
## 2288 2020-04-07 South West 39
## 2289 2020-04-08 South West 47
## 2290 2020-04-09 South West 24
## 2291 2020-04-10 South West 46
## 2292 2020-04-11 South West 43
## 2293 2020-04-12 South West 23
## 2294 2020-04-13 South West 28
## 2295 2020-04-14 South West 24
## 2296 2020-04-15 South West 32
## 2297 2020-04-16 South West 29
## 2298 2020-04-17 South West 33
## 2299 2020-04-18 South West 25
## 2300 2020-04-19 South West 31
## 2301 2020-04-20 South West 26
## 2302 2020-04-21 South West 26
## 2303 2020-04-22 South West 23
## 2304 2020-04-23 South West 17
## 2305 2020-04-24 South West 19
## 2306 2020-04-25 South West 15
## 2307 2020-04-26 South West 27
## 2308 2020-04-27 South West 13
## 2309 2020-04-28 South West 17
## 2310 2020-04-29 South West 15
## 2311 2020-04-30 South West 26
## 2312 2020-05-01 South West 6
## 2313 2020-05-02 South West 7
## 2314 2020-05-03 South West 10
## 2315 2020-05-04 South West 17
## 2316 2020-05-05 South West 14
## 2317 2020-05-06 South West 19
## 2318 2020-05-07 South West 16
## 2319 2020-05-08 South West 6
## 2320 2020-05-09 South West 11
## 2321 2020-05-10 South West 5
## 2322 2020-05-11 South West 8
## 2323 2020-05-12 South West 7
## 2324 2020-05-13 South West 7
## 2325 2020-05-14 South West 6
## 2326 2020-05-15 South West 4
## 2327 2020-05-16 South West 4
## 2328 2020-05-17 South West 6
## 2329 2020-05-18 South West 4
## 2330 2020-05-19 South West 6
## 2331 2020-05-20 South West 1
## 2332 2020-05-21 South West 9
## 2333 2020-05-22 South West 7
## 2334 2020-05-23 South West 6
## 2335 2020-05-24 South West 3
## 2336 2020-05-25 South West 8
## 2337 2020-05-26 South West 11
## 2338 2020-05-27 South West 5
## 2339 2020-05-28 South West 10
## 2340 2020-05-29 South West 7
## 2341 2020-05-30 South West 3
## 2342 2020-05-31 South West 2
## 2343 2020-06-01 South West 7
## 2344 2020-06-02 South West 2
## 2345 2020-06-03 South West 7
## 2346 2020-06-04 South West 2
## 2347 2020-06-05 South West 2
## 2348 2020-06-06 South West 1
## 2349 2020-06-07 South West 3
## 2350 2020-06-08 South West 3
## 2351 2020-06-09 South West 0
## 2352 2020-06-10 South West 1
## 2353 2020-06-11 South West 2
## 2354 2020-06-12 South West 2
## 2355 2020-06-13 South West 2
## 2356 2020-06-14 South West 0
## 2357 2020-06-15 South West 2
## 2358 2020-06-16 South West 2
## 2359 2020-06-17 South West 0
## 2360 2020-06-18 South West 0
## 2361 2020-06-19 South West 0
## 2362 2020-06-20 South West 2
## 2363 2020-06-21 South West 0
## 2364 2020-06-22 South West 1
## 2365 2020-06-23 South West 1
## 2366 2020-06-24 South West 1
## 2367 2020-06-25 South West 0
## 2368 2020-06-26 South West 3
## 2369 2020-06-27 South West 0
## 2370 2020-06-28 South West 0
## 2371 2020-06-29 South West 1
## 2372 2020-06-30 South West 0
## 2373 2020-07-01 South West 0
## 2374 2020-07-02 South West 0
## 2375 2020-07-03 South West 0
## 2376 2020-07-04 South West 0
## 2377 2020-07-05 South West 1
## 2378 2020-07-06 South West 0
## 2379 2020-07-07 South West 0
## 2380 2020-07-08 South West 2
## 2381 2020-07-09 South West 0
## 2382 2020-07-10 South West 1
## 2383 2020-07-11 South West 0
## 2384 2020-07-12 South West 0
## 2385 2020-07-13 South West 1
## 2386 2020-07-14 South West 0
## 2387 2020-07-15 South West 0
## 2388 2020-07-16 South West 0
## 2389 2020-07-17 South West 1
## 2390 2020-07-18 South West 0
## 2391 2020-07-19 South West 0
## 2392 2020-07-20 South West 0
## 2393 2020-07-21 South West 0
## 2394 2020-07-22 South West 0
## 2395 2020-07-23 South West 0
## 2396 2020-07-24 South West 0
## 2397 2020-07-25 South West 0
## 2398 2020-07-26 South West 0
## 2399 2020-07-27 South West 0
## 2400 2020-07-28 South West 0
## 2401 2020-07-29 South West 0
## 2402 2020-07-30 South West 1
## 2403 2020-07-31 South West 0
## 2404 2020-08-01 South West 0
## 2405 2020-08-02 South West 0
## 2406 2020-08-03 South West 0
## 2407 2020-08-04 South West 0
## 2408 2020-08-05 South West 0
## 2409 2020-08-06 South West 0
## 2410 2020-08-07 South West 0
## 2411 2020-08-08 South West 0
## 2412 2020-08-09 South West 0
## 2413 2020-08-10 South West 0
## 2414 2020-08-11 South West 0
## 2415 2020-08-12 South West 0
## 2416 2020-08-13 South West 0
## 2417 2020-08-14 South West 1
## 2418 2020-08-15 South West 0
## 2419 2020-08-16 South West 0
## 2420 2020-08-17 South West 2
## 2421 2020-08-18 South West 0
## 2422 2020-08-19 South West 0
## 2423 2020-08-20 South West 0
## 2424 2020-08-21 South West 0
## 2425 2020-08-22 South West 0
## 2426 2020-08-23 South West 0
## 2427 2020-08-24 South West 0
## 2428 2020-08-25 South West 1
## 2429 2020-08-26 South West 0
## 2430 2020-08-27 South West 1
## 2431 2020-08-28 South West 0
## 2432 2020-08-29 South West 0
## 2433 2020-08-30 South West 0
## 2434 2020-08-31 South West 0
## 2435 2020-09-01 South West 0
## 2436 2020-09-02 South West 0
## 2437 2020-09-03 South West 0
## 2438 2020-09-04 South West 0
## 2439 2020-09-05 South West 0
## 2440 2020-09-06 South West 0
## 2441 2020-09-07 South West 0
## 2442 2020-09-08 South West 1
## 2443 2020-09-09 South West 0
## 2444 2020-09-10 South West 0
## 2445 2020-09-11 South West 0
## 2446 2020-09-12 South West 0
## 2447 2020-09-13 South West 1
## 2448 2020-09-14 South West 0
## 2449 2020-09-15 South West 0
## 2450 2020-09-16 South West 0
## 2451 2020-09-17 South West 1
## 2452 2020-09-18 South West 0
## 2453 2020-09-19 South West 0
## 2454 2020-09-20 South West 1
## 2455 2020-09-21 South West 0
## 2456 2020-09-22 South West 0
## 2457 2020-09-23 South West 0
## 2458 2020-09-24 South West 1
## 2459 2020-09-25 South West 0
## 2460 2020-09-26 South West 0
## 2461 2020-09-27 South West 0
## 2462 2020-09-28 South West 0
## 2463 2020-09-29 South West 0
## 2464 2020-09-30 South West 0
## 2465 2020-10-01 South West 0
## 2466 2020-10-02 South West 1
## 2467 2020-10-03 South West 0
## 2468 2020-10-04 South West 0
## 2469 2020-10-05 South West 0
## 2470 2020-10-06 South West 1
## 2471 2020-10-07 South West 0
## 2472 2020-10-08 South West 1
## 2473 2020-10-09 South West 1
## 2474 2020-10-10 South West 0
## 2475 2020-10-11 South West 4
## 2476 2020-10-12 South West 2
## 2477 2020-10-13 South West 0
## 2478 2020-10-14 South West 3
## 2479 2020-10-15 South West 1
## 2480 2020-10-16 South West 2
## 2481 2020-10-17 South West 8
## 2482 2020-10-18 South West 2
## 2483 2020-10-19 South West 2
## 2484 2020-10-20 South West 3
## 2485 2020-10-21 South West 6
## 2486 2020-10-22 South West 6
## 2487 2020-10-23 South West 5
## 2488 2020-10-24 South West 5
## 2489 2020-10-25 South West 5
## 2490 2020-10-26 South West 7
## 2491 2020-10-27 South West 6
## 2492 2020-10-28 South West 8
## 2493 2020-10-29 South West 11
## 2494 2020-10-30 South West 8
## 2495 2020-10-31 South West 5
## 2496 2020-11-01 South West 5
## 2497 2020-11-02 South West 11
## 2498 2020-11-03 South West 7
## 2499 2020-11-04 South West 8
## 2500 2020-11-05 South West 5
## 2501 2020-11-06 South West 11
## 2502 2020-11-07 South West 10
## 2503 2020-11-08 South West 10
## 2504 2020-11-09 South West 12
## 2505 2020-11-10 South West 6
## 2506 2020-11-11 South West 13
## 2507 2020-11-12 South West 17
## 2508 2020-11-13 South West 9
## 2509 2020-11-14 South West 8
## 2510 2020-11-15 South West 16
## 2511 2020-11-16 South West 18
## 2512 2020-11-17 South West 17
## 2513 2020-11-18 South West 26
## 2514 2020-11-19 South West 15
## 2515 2020-11-20 South West 25
## 2516 2020-11-21 South West 25
## 2517 2020-11-22 South West 24
## 2518 2020-11-23 South West 14
## 2519 2020-11-24 South West 20
## 2520 2020-11-25 South West 25
## 2521 2020-11-26 South West 16
## 2522 2020-11-27 South West 21
## 2523 2020-11-28 South West 35
## 2524 2020-11-29 South West 15
## 2525 2020-11-30 South West 22
## 2526 2020-12-01 South West 19
## 2527 2020-12-02 South West 15
## 2528 2020-12-03 South West 14
## 2529 2020-12-04 South West 20
## 2530 2020-12-05 South West 17
## 2531 2020-12-06 South West 13
## 2532 2020-12-07 South West 16
## 2533 2020-12-08 South West 19
## 2534 2020-12-09 South West 22
## 2535 2020-12-10 South West 21
## 2536 2020-12-11 South West 20
## 2537 2020-12-12 South West 15
## 2538 2020-12-13 South West 19
## 2539 2020-12-14 South West 20
## 2540 2020-12-15 South West 20
## 2541 2020-12-16 South West 9
## 2542 2020-12-17 South West 26
## 2543 2020-12-18 South West 11
## 2544 2020-12-19 South West 22
## 2545 2020-12-20 South West 19
## 2546 2020-12-21 South West 22
## 2547 2020-12-22 South West 11
## 2548 2020-12-23 South West 16
## 2549 2020-12-24 South West 18
## 2550 2020-12-25 South West 19
## 2551 2020-12-26 South West 24
## 2552 2020-12-27 South West 24
## 2553 2020-12-28 South West 21
## 2554 2020-12-29 South West 20
## 2555 2020-12-30 South West 17
## 2556 2020-12-31 South West 28
## 2557 2021-01-01 South West 29
## 2558 2021-01-02 South West 24
## 2559 2021-01-03 South West 28
## 2560 2021-01-04 South West 33
## 2561 2021-01-05 South West 31
## 2562 2021-01-06 South West 27
## 2563 2021-01-07 South West 31
## 2564 2021-01-08 South West 34
## 2565 2021-01-09 South West 26
## 2566 2021-01-10 South West 34
## 2567 2021-01-11 South West 40
## 2568 2021-01-12 South West 53
## 2569 2021-01-13 South West 43
## 2570 2021-01-14 South West 39
## 2571 2021-01-15 South West 47
## 2572 2021-01-16 South West 57
## 2573 2021-01-17 South West 42
## 2574 2021-01-18 South West 47
## 2575 2021-01-19 South West 45
## 2576 2021-01-20 South West 65
## 2577 2021-01-21 South West 62
## 2578 2021-01-22 South West 60
## 2579 2021-01-23 South West 54
## 2580 2021-01-24 South West 59
## 2581 2021-01-25 South West 62
## 2582 2021-01-26 South West 47
## 2583 2021-01-27 South West 46
## 2584 2021-01-28 South West 52
## 2585 2021-01-29 South West 42
## 2586 2021-01-30 South West 39
## 2587 2021-01-31 South West 36
## 2588 2021-02-01 South West 29
## 2589 2021-02-02 South West 38
## 2590 2021-02-03 South West 32
## 2591 2021-02-04 South West 33
## 2592 2021-02-05 South West 25
## 2593 2021-02-06 South West 39
## 2594 2021-02-07 South West 35
## 2595 2021-02-08 South West 32
## 2596 2021-02-09 South West 31
## 2597 2021-02-10 South West 18
## 2598 2021-02-11 South West 19
## 2599 2021-02-12 South West 28
## 2600 2021-02-13 South West 29
## 2601 2021-02-14 South West 17
## 2602 2021-02-15 South West 21
## 2603 2021-02-16 South West 12
## 2604 2021-02-17 South West 20
## 2605 2021-02-18 South West 21
## 2606 2021-02-19 South West 18
## 2607 2021-02-20 South West 12
## 2608 2021-02-21 South West 16
## 2609 2021-02-22 South West 11
## 2610 2021-02-23 South West 6
## 2611 2021-02-24 South West 9
## 2612 2021-02-25 South West 12
## 2613 2021-02-26 South West 6
## 2614 2021-02-27 South West 6
## 2615 2021-02-28 South West 10
## 2616 2021-03-01 South West 15
## 2617 2021-03-02 South West 8
## 2618 2021-03-03 South West 3
## 2619 2021-03-04 South West 4
## 2620 2021-03-05 South West 4
## 2621 2021-03-06 South West 6
## 2622 2021-03-07 South West 1
## 2623 2021-03-08 South West 8
## 2624 2021-03-09 South West 0
## 2625 2021-03-10 South West 01.5 Completion date
We extract the completion date from the NHS Pathways file timestamp:
The completion date of the NHS Pathways data is Thursday 11 Mar 2021.
1.6 Auxiliary functions
These are functions which will be used further in the analyses.
Function to estimate the generalised R-squared as the proportion of deviance explained by a given model:
## Function to calculate R2 for Poisson model
## not adjusted for model complexity but all models have the same DF here
Rsq <- function(x) {
1 - (x$deviance / x$null.deviance)
}Function to extract growth rates per region as well as halving times, and the associated 95% confidence intervals:
## function to extract the coefficients, find the level of the intercept,
## reconstruct the values of r, get confidence intervals
get_r <- function(model) {
## extract coefficients and conf int
out <- data.frame(r = coef(model)) %>%
rownames_to_column("var") %>%
cbind(confint(model)) %>%
filter(!grepl("day_of_week", var)) %>%
filter(grepl("day", var)) %>%
rename(lower_95 = "2.5 %",
upper_95 = "97.5 %") %>%
mutate(var = sub("day:", "", var))
## reconstruct values: intercept + region-coefficient
for (i in 2:nrow(out)) {
out[i, -1] <- out[1, -1] + out[i, -1]
}
## find the name of the intercept, restore regions names
out <- out %>%
mutate(nhs_region = model$xlevels$nhs_region) %>%
select(nhs_region, everything(), -var)
## find halving times
halving <- log(0.5) / out[,-1] %>%
rename(halving_t = r,
halving_t_lower_95 = lower_95,
halving_t_upper_95 = upper_95)
## set halving times with exclusion intervals to NA
no_halving <- out$lower_95 < 0 & out$upper_95 > 0
halving[no_halving, ] <- NA_real_
## return all data
cbind(out, halving)
}Functions used in the correlation analysis between NHS Pathways reports and deaths:
## Function to calculate Pearson's correlation between deaths and lagged
## reports. Note that `pearson` can be replaced with `spearman` for rank
## correlation.
getcor <- function(x, ndx) {
return(cor(x$deaths[ndx],
x$note_lag[ndx],
use = "complete.obs",
method = "pearson"))
}
## Catch if sample size throws an error
getcor2 <- possibly(getcor, otherwise = NA)
getboot <- function(x) {
result <- boot::boot.ci(boot::boot(x, getcor2, R = 1000),
type = "bca")
return(data.frame(n = sum(!is.na(x$note_lag) & !is.na(x$deaths)),
r = result$t0,
r_low = result$bca[4],
r_hi = result$bca[5]))
}Function to classify the day of the week into weekend, Monday, and the rest:
## Fn to add day of week
day_of_week <- function(df) {
df %>%
dplyr::mutate(day_of_week = lubridate::wday(date, label = TRUE)) %>%
dplyr::mutate(day_of_week = dplyr::case_when(
day_of_week %in% c("Sat", "Sun") ~ "weekend",
day_of_week %in% c("Mon") ~ "monday",
!(day_of_week %in% c("Sat", "Sun", "Mon")) ~ "rest_of_week"
) %>%
factor(levels = c("rest_of_week", "monday", "weekend")))
}Custom color palettes, color scales, and vectors of colors:
2 Temporal trends in NHS Pathways reports
2.1 Outline
We look for temporal patterns in COVID-19 related 111/999 calls and 111 online reports. Analyses are broken down by NHS region. We also look for estimates of recent growth rate and associated doubling / halving time.
2.2 Reports by region over time
tab_date_region_all <- x %>%
filter(!is.na(nhs_region)) %>%
group_by(date, nhs_region) %>%
summarise(n = sum(count))
dth %>%
mutate(trusted = case_when(date_report < max(dth$date_report)-delay_max ~ "Y",
date_report >= max(dth$date_report)-delay_max ~ "N"),
value = "Deaths",
vline = max(dth$date_report)-delay_max-1,
lab = "Truncated for reporting delay",
lab_pos_x = vline + 10,
lab_pos_y = 150,
lab_col = "darkgrey") %>%
rename(date = date_report,
n = deaths) %>%
bind_rows(
mutate(tab_date_region_all, value = "Reports",
trusted = "Y",
vline = as.Date("2020-03-23"),
lab = "Start of UK lockdown",
lab_pos_x = vline - 8,
lab_pos_y = 30200,
lab_col = "black")
) %>%
mutate(value = factor(value, levels = c("Reports","Deaths"))) -> dths_reports
plot_dth_report <-
ggplot(dths_reports, aes(date, n, colour = nhs_region)) +
# Add main points and lines, coloured by region and fade out deaths for excluded period
geom_point(aes(alpha = trusted)) +
geom_line(alpha = 0.2) +
geom_smooth(method = "loess", span = .5, color = "black") +
scale_colour_manual("", values = pal) +
scale_alpha_manual(values = c(0.3,1)) +
guides(alpha = F) +
# Add vertical markers for important dates with labels - different for each facet
ggnewscale::new_scale_colour() +
geom_vline(aes(xintercept = vline, col = value), lty = "solid") +
geom_text(aes(x = lab_pos_x, y = lab_pos_y, label = lab, col = value), size = 3) +
scale_colour_manual("",values = c("black","darkgrey"), guide = F) +
# Facet by deaths and reports
facet_grid(rows = vars(value), scales = "free_y", switch = "y") +
# Other formatting
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",strip.placement = "outside") +
rotate_x +
labs(x = NULL,
y = NULL)
plot_dth_report
2.3 Reports by region by age over time
We plot the number of 111/999 calls and 111 online reports by age, and the proportion of 111/999 calls and 111 online reports by age. In the second graph, the vertical lines indicate the proportion of individuals residing in the corresponding NHS region who belong to the corresponding age group.
tab_date_region_age_all <- x %>%
filter(!is.na(nhs_region),
age != "missing") %>%
group_by(date, nhs_region, age) %>%
summarise(n = sum(count))
tab_date_region_age_all %>%
ggplot(aes(x = date, y = n, fill = age)) +
geom_col(position = "stack") +
scale_fill_manual(values = age.pal) +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
axis.text.x = element_text(angle = 90, hjust = 1)) +
guides(fill = guide_legend(title = "Age", ncol = 3)) +
labs(x = NULL,
y = "Total daily reports by age") +
facet_wrap(~ nhs_region, ncol = 4)
tab_date_region_age_all <- tab_date_region_age_all %>%
group_by(date, nhs_region) %>%
summarise(tot = sum(n)) %>%
left_join(tab_date_region_age_all, by = c("date", "nhs_region")) %>%
mutate(prop_n = n/tot)
tab_date_region_age_all %>%
ggplot(aes(x = date, y = prop_n, color = age)) +
scale_color_manual(values = age.pal) +
geom_line() +
geom_point() +
geom_hline(data = nhs_region_pop, aes(yintercept = value, color = variable)) +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
axis.text.x = element_text(angle = 90, hjust = 1)) +
guides(color = guide_legend(title = "Age", ncol = 3)) +
labs(x = NULL,
y = "Proportion of daily reports by age") +
facet_wrap(~ nhs_region, ncol = 4)
2.4 Moving window model
We fit quasi-Poisson GLMs for 14-day windows to get growth rates over time.
## set moving time window (1/2/3 weeks)
w <- 14
# create empty df
r_all_sliding <- NULL
## make data for model
x_model_all_moving <- x %>%
filter(!is.na(nhs_region)) %>%
group_by(date, nhs_region) %>%
summarise(n = sum(count))
unique_dates <- unique(x_model_all_moving$date)
for (i in 1:(length(unique_dates) - w)) {
date_i <- unique_dates[i]
date_i_max <- date_i + w
model_data <- x_model_all_moving %>%
filter(date >= date_i & date < date_i_max) %>%
mutate(day = as.integer(date - date_i)) %>%
day_of_week()
mod <- glm(n ~ day * nhs_region + day_of_week,
data = model_data,
family = 'quasipoisson')
# get growth rate
r <- get_r(mod)
r$w_min <- date_i
r$w_max <- date_i_max
# combine all estimates
r_all_sliding <- bind_rows(r_all_sliding, r)
}
#serial interval distribution
SI_param = epitrix::gamma_mucv2shapescale(4.7, 2.9/4.7)
SI_distribution <- distcrete::distcrete("gamma", interval = 1,
shape = SI_param$shape,
scale = SI_param$scale,
w = 0.5)
#convert growth rates r to R0
r_all_sliding <- r_all_sliding %>%
mutate(R = epitrix::r2R0(r, SI_distribution),
R_lower_95 = epitrix::r2R0(lower_95, SI_distribution),
R_upper_95 = epitrix::r2R0(upper_95, SI_distribution))We examine the evolution of the growth rate by region over time.
# plot
plot_growth <-
r_all_sliding %>%
ggplot(aes(x = w_max, y = r)) +
geom_ribbon(aes(ymin = lower_95, ymax = upper_95, fill = nhs_region), alpha = 0.1) +
geom_line(aes(colour = nhs_region)) +
geom_point(aes(colour = nhs_region)) +
geom_hline(yintercept = 0, linetype = "dashed") +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
plot.margin = margin(0.5,1,0.5,0.5, "cm")) +
guides(colour = guide_legend(title = "", override.aes = list(fill = NA)), fill = FALSE) +
labs(x = "",
y = "Estimated daily growth rate (r)") +
scale_colour_manual(values = pal)From the growth rate, we derive R and examine its value through time.
# plot
plot_R <-
r_all_sliding %>%
ggplot(aes(x = w_max, y = R)) +
geom_ribbon(aes(ymin = R_lower_95, ymax = R_upper_95, fill = nhs_region), alpha = 0.1) +
geom_line(aes(colour = nhs_region)) +
geom_point(aes(colour = nhs_region)) +
geom_hline(yintercept = 1, linetype = "dashed") +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
plot.margin = margin(0.5,1,0.5,0.5, "cm")) +
guides(color = guide_legend(title = "", override.aes = list(fill = NA)), fill = FALSE) +
labs(x = "",
y = "Estimated effective reproduction\nnumber (Re)") +
scale_colour_manual(values = pal)
R <- r_all_sliding %>%
mutate(lower_95 = R_lower_95,
upper_95 = R_upper_95,
value = R,
measure = "R",
reference = 1)
r_R <- r_all_sliding %>%
mutate(measure = "r",
value = r,
reference = 0) %>%
bind_rows(R)
r_R %>%
ggplot(aes(x = w_max, y = value)) +
geom_ribbon(aes(ymin = lower_95, ymax = upper_95, fill = nhs_region), alpha = 0.1) +
geom_line(aes(colour = nhs_region)) +
geom_point(aes(colour = nhs_region)) +
geom_hline(aes(yintercept = reference), linetype = "dashed") +
theme_bw() +
scale_weeks +
rotate_x +
theme(legend.position = "bottom",
plot.margin = margin(0.5,1,0,0, "cm"),
strip.background = element_blank(),
# strip.text.x = element_blank(),
strip.placement = "outside"
) +
guides(color = guide_legend(title = "",
override.aes = list(fill = NA)),
fill = FALSE) +
labs(x = "", y = "") +
scale_colour_manual(values = pal) +
facet_grid(rows = vars(measure),
scales = "free_y",
switch = "y",
labeller = as_labeller(c(r = "Daily growth rate (r)",
R = "Effective reproduction\nnumber (Re)")))
2.5 Moving window model - stratified by age
We repeat the above analysis, where we fit quasi-Poisson GLMs for 14-day windows to get growth rates over time, but apply this to each age group separately (0-18, 19-69, 70-120 years old).
We first run the analysis for 0-18 years old.
## set moving time window (2 weeks)
w <- 14
# create empty df
r_all_sliding_0_18 <- NULL
## make data for model
x_model_all_moving_0_18 <- x %>%
filter(!is.na(nhs_region),
age == "0-18") %>%
group_by(date, nhs_region) %>%
summarise(n = sum(count))
unique_dates <- unique(x_model_all_moving_0_18$date)
for (i in 1:(length(unique_dates) - w)) {
date_i <- unique_dates[i]
date_i_max <- date_i + w
model_data <- x_model_all_moving_0_18 %>%
filter(date >= date_i & date < date_i_max) %>%
mutate(day = as.integer(date - date_i)) %>%
day_of_week()
mod <- glm(n ~ day * nhs_region + day_of_week,
data = model_data,
family = 'quasipoisson')
# get growth rate
r <- get_r(mod)
r$w_min <- date_i
r$w_max <- date_i_max
# combine all estimates
r_all_sliding_0_18 <- bind_rows(r_all_sliding_0_18, r)
}
#serial interval distribution
SI_param = epitrix::gamma_mucv2shapescale(4.7, 2.9/4.7)
SI_distribution <- distcrete::distcrete("gamma", interval = 1,
shape = SI_param$shape,
scale = SI_param$scale, w = 0.5)
#convert growth rates r to R0
r_all_sliding_0_18 <- r_all_sliding_0_18 %>%
mutate(R = epitrix::r2R0(r, SI_distribution),
R_lower_95 = epitrix::r2R0(lower_95, SI_distribution),
R_upper_95 = epitrix::r2R0(upper_95, SI_distribution))# plot
plot_growth <-
r_all_sliding_0_18 %>%
ggplot(aes(x = w_max, y = r)) +
geom_ribbon(aes(ymin = lower_95, ymax = upper_95, fill = nhs_region), alpha = 0.1) +
geom_line(aes(colour = nhs_region)) +
geom_point(aes(colour = nhs_region)) +
geom_hline(yintercept = 0, linetype = "dashed") +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
plot.margin = margin(0.5,1,0.5,0.5, "cm")) +
guides(colour = guide_legend(title = "",override.aes = list(fill = NA)), fill = FALSE) +
labs(x = "",
y = "Estimated daily growth rate (r)"
) +
scale_colour_manual(values = pal)# plot
plot_R <-
r_all_sliding_0_18 %>%
ggplot(aes(x = w_max, y = R)) +
geom_ribbon(aes(ymin = R_lower_95, ymax = R_upper_95, fill = nhs_region), alpha = 0.1) +
geom_line(aes(colour = nhs_region)) +
geom_point(aes(colour = nhs_region)) +
geom_hline(yintercept = 1, linetype = "dashed") +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
plot.margin = margin(0.5,1,0.5,0.5, "cm")) +
guides(color = guide_legend(title = "", override.aes = list(fill = NA)), fill = FALSE) +
labs(x = "",
y = "Estimated effective reproduction\nnumber (Re)"
) +
scale_colour_manual(values = pal)
R <- r_all_sliding_0_18 %>%
mutate(lower_95 = R_lower_95,
upper_95 = R_upper_95,
value = R,
measure = "R",
reference = 1)
r_R <- r_all_sliding_0_18 %>%
mutate(measure = "r",
value = r,
reference = 0) %>%
bind_rows(R)
fig2_3_0_18 <- r_R %>%
ggplot(aes(x = w_max, y = value)) +
geom_ribbon(aes(ymin = lower_95, ymax = upper_95, fill = nhs_region), alpha = 0.1) +
geom_line(aes(colour = nhs_region)) +
geom_point(aes(colour = nhs_region)) +
geom_hline(aes(yintercept = reference), linetype = "dashed") +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
plot.margin = margin(0.5,1,0,0, "cm"),
strip.background = element_blank(),
strip.placement = "outside"
) +
guides(color = guide_legend(title = "", override.aes = list(fill = NA)), fill = FALSE) +
labs(x = "", y = "") +
scale_colour_manual(values = pal) +
facet_grid(rows = vars(measure),
scales = "free_y",
switch = "y",
labeller = as_labeller(c(r = "Daily growth rate (r)",
R = "Effective reproduction\nnumber (Re)")))Then, we run the analysis for 19-69 years old.
## set moving time window (2 weeks)
w <- 14
# create empty df
r_all_sliding_19_69 <- NULL
## make data for model
x_model_all_moving_19_69 <- x %>%
filter(!is.na(nhs_region),
age == "19-69") %>%
group_by(date, nhs_region) %>%
summarise(n = sum(count))
unique_dates <- unique(x_model_all_moving_19_69$date)
for (i in 1:(length(unique_dates) - w)) {
date_i <- unique_dates[i]
date_i_max <- date_i + w
model_data <- x_model_all_moving_19_69 %>%
filter(date >= date_i & date < date_i_max) %>%
mutate(day = as.integer(date - date_i)) %>%
day_of_week()
mod <- glm(n ~ day * nhs_region + day_of_week,
data = model_data,
family = 'quasipoisson')
# get growth rate
r <- get_r(mod)
r$w_min <- date_i
r$w_max <- date_i_max
# combine all estimates
r_all_sliding_19_69 <- bind_rows(r_all_sliding_19_69, r)
}
#serial interval distribution
SI_param = epitrix::gamma_mucv2shapescale(4.7, 2.9/4.7)
SI_distribution <- distcrete::distcrete("gamma", interval = 1,
shape = SI_param$shape,
scale = SI_param$scale, w = 0.5)
#convert growth rates r to R0
r_all_sliding_19_69 <- r_all_sliding_19_69 %>%
mutate(R = epitrix::r2R0(r, SI_distribution),
R_lower_95 = epitrix::r2R0(lower_95, SI_distribution),
R_upper_95 = epitrix::r2R0(upper_95, SI_distribution))# plot
plot_growth <-
r_all_sliding_19_69 %>%
ggplot(aes(x = w_max, y = r)) +
geom_ribbon(aes(ymin = lower_95, ymax = upper_95, fill = nhs_region), alpha = 0.1) +
geom_line(aes(colour = nhs_region)) +
geom_point(aes(colour = nhs_region)) +
geom_hline(yintercept = 0, linetype = "dashed") +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
plot.margin = margin(0.5,1,0.5,0.5, "cm")) +
guides(colour = guide_legend(title = "", override.aes = list(fill = NA)), fill = FALSE) +
labs(x = "",
y = "Estimated daily growth rate (r)") +
scale_colour_manual(values = pal)# plot
plot_R <-
r_all_sliding_19_69 %>%
ggplot(aes(x = w_max, y = R)) +
geom_ribbon(aes(ymin = R_lower_95, ymax = R_upper_95, fill = nhs_region), alpha = 0.1) +
geom_line(aes(colour = nhs_region)) +
geom_point(aes(colour = nhs_region)) +
geom_hline(yintercept = 1, linetype = "dashed") +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
plot.margin = margin(0.5,1,0.5,0.5, "cm")) +
guides(color = guide_legend(title = "", override.aes = list(fill = NA)), fill = FALSE) +
labs(x = "",
y = "Estimated effective reproduction\nnumber (Re)"
) +
scale_colour_manual(values = pal)
R <- r_all_sliding_19_69 %>%
mutate(lower_95 = R_lower_95,
upper_95 = R_upper_95,
value = R,
measure = "R",
reference = 1)
r_R <- r_all_sliding_19_69 %>%
mutate(measure = "r",
value = r,
reference = 0) %>%
bind_rows(R)
fig2_3_19_69 <- r_R %>%
ggplot(aes(x = w_max, y = value)) +
geom_ribbon(aes(ymin = lower_95, ymax = upper_95, fill = nhs_region), alpha = 0.1) +
geom_line(aes(colour = nhs_region)) +
geom_point(aes(colour = nhs_region)) +
geom_hline(aes(yintercept = reference), linetype = "dashed") +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
plot.margin = margin(0.5,1,0,0, "cm"),
strip.background = element_blank(),
strip.placement = "outside"
) +
guides(color = guide_legend(title = "", override.aes = list(fill = NA)), fill = FALSE) +
labs(x = "", y = "") +
scale_colour_manual(values = pal) +
facet_grid(rows = vars(measure),
scales = "free_y",
switch = "y",
labeller = as_labeller(c(r = "Daily growth rate (r)",
R = "Effective reproduction\nnumber (Re)")))Finally, we run the analysis for 70-120 years old.
## set moving time window (2 weeks)
w <- 14
# create empty df
r_all_sliding_70_120 <- NULL
## make data for model
x_model_all_moving_70_120 <- x %>%
filter(!is.na(nhs_region),
age == "70-120") %>%
group_by(date, nhs_region) %>%
summarise(n = sum(count))
unique_dates <- unique(x_model_all_moving_70_120$date)
for (i in 1:(length(unique_dates) - w)) {
date_i <- unique_dates[i]
date_i_max <- date_i + w
model_data <- x_model_all_moving_70_120 %>%
filter(date >= date_i & date < date_i_max) %>%
mutate(day = as.integer(date - date_i)) %>%
day_of_week()
mod <- glm(n ~ day * nhs_region + day_of_week,
data = model_data,
family = 'quasipoisson')
# get growth rate
r <- get_r(mod)
r$w_min <- date_i
r$w_max <- date_i_max
# combine all estimates
r_all_sliding_70_120 <- bind_rows(r_all_sliding_70_120, r)
}
#serial interval distribution
SI_param = epitrix::gamma_mucv2shapescale(4.7, 2.9/4.7)
SI_distribution <- distcrete::distcrete("gamma", interval = 1,
shape = SI_param$shape,
scale = SI_param$scale, w = 0.5)
#convert growth rates r to R0
r_all_sliding_70_120 <- r_all_sliding_70_120 %>%
mutate(R = epitrix::r2R0(r, SI_distribution),
R_lower_95 = epitrix::r2R0(lower_95, SI_distribution),
R_upper_95 = epitrix::r2R0(upper_95, SI_distribution))# plot
plot_growth <-
r_all_sliding_70_120 %>%
ggplot(aes(x = w_max, y = r)) +
geom_ribbon(aes(ymin = lower_95, ymax = upper_95, fill = nhs_region), alpha = 0.1) +
geom_line(aes(colour = nhs_region)) +
geom_point(aes(colour = nhs_region)) +
geom_hline(yintercept = 0, linetype = "dashed") +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
plot.margin = margin(0.5,1,0.5,0.5, "cm")) +
guides(colour = guide_legend(title = "",override.aes = list(fill = NA)), fill = FALSE) +
labs(x = "",
y = "Estimated daily growth rate (r)"
) +
scale_colour_manual(values = pal)# plot
plot_R <-
r_all_sliding_70_120 %>%
ggplot(aes(x = w_max, y = R)) +
geom_ribbon(aes(ymin = R_lower_95, ymax = R_upper_95, fill = nhs_region), alpha = 0.1) +
geom_line(aes(colour = nhs_region)) +
geom_point(aes(colour = nhs_region)) +
geom_hline(yintercept = 1, linetype = "dashed") +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
plot.margin = margin(0.5,1,0.5,0.5, "cm")) +
guides(color = guide_legend(title = "", override.aes = list(fill = NA)), fill = FALSE) +
labs(x = "",
y = "Estimated effective reproduction\nnumber (Re)") +
scale_colour_manual(values = pal)
R <- r_all_sliding_70_120 %>%
mutate(lower_95 = R_lower_95,
upper_95 = R_upper_95,
value = R,
measure = "R",
reference = 1)
r_R <- r_all_sliding_70_120 %>%
mutate(measure = "r",
value = r,
reference = 0) %>%
bind_rows(R)
fig2_3_70_120 <- r_R %>%
ggplot(aes(x = w_max, y = value)) +
geom_ribbon(aes(ymin = lower_95, ymax = upper_95, fill = nhs_region), alpha = 0.1) +
geom_line(aes(colour = nhs_region)) +
geom_point(aes(colour = nhs_region)) +
geom_hline(aes(yintercept = reference), linetype = "dashed") +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
plot.margin = margin(0.5,1,0,0, "cm"),
strip.background = element_blank(),
strip.placement = "outside"
) +
guides(color = guide_legend(title = "", override.aes = list(fill = NA)), fill = FALSE) +
labs(x = "", y = "") +
scale_colour_manual(values = pal) +
facet_grid(rows = vars(measure),
scales = "free_y",
switch = "y",
labeller = as_labeller(c(r = "Daily growth rate (r)",
R = "Effective reproduction\nnumber (Re)"))) We combine the estimated growth rates and effective reproduction numbers into a single figure.
ggpubr::ggarrange(fig2_3_0_18,
fig2_3_19_69,
fig2_3_70_120,
nrow = 3,
labels = "AUTO",
common.legend = TRUE,
legend = "bottom",
align = "hv") 
3 Comparison with deaths time series
3.1 Outline
We want to explore the correlation between NHS Pathways reports and deaths, and assess the potential for reports to be used as an early warning system for disease resurgence.
Death data are publically available. We truncate the time series to avoid bias from reporting delay - we assume a conservative delay of three weeks.
3.2 Lagged correlation
We calculate Pearson’s correlation coefficient between deaths and NHS Pathways notifications using different lags. Confidence intervals are obtained using bootstrap. Note that results were also confirmed using Spearman’s rank correlation.
First we join the NHS Pathways and death data, and aggregate over all England:
## truncate death data for reporting delay
trunc_date <- max(dth$date_report) - delay_max
dth_trunc <- dth %>%
rename(date = date_report) %>%
filter(date <= trunc_date)
## join with notification data
all_data <- x %>%
filter(!is.na(nhs_region)) %>%
group_by(date, nhs_region) %>%
summarise(count = sum(count, na.rm = T)) %>%
ungroup %>%
inner_join(dth_trunc,
by = c("date","nhs_region"))
all_tot <- all_data %>%
group_by(date) %>%
summarise(count = sum(count, na.rm = TRUE),
deaths = sum(deaths, na.rm = TRUE)) We calculate correlation with lagged NHS Pathways reports from 0 to 30 days behind deaths:
## Calculate all correlations + bootstrap CIs
lag_cor <- data.frame()
for (i in 0:30) {
## lag reports
summary <- all_tot %>%
mutate(note_lag = lag(count, i)) %>%
## calculate rank correlation and bootstrap CI
getboot(.) %>%
mutate(lag = i)
lag_cor <- bind_rows(lag_cor, summary)
}
cor_vs_lag <- ggplot(lag_cor, aes(lag, r)) +
theme_bw() +
geom_ribbon(aes(ymin = r_low, ymax = r_hi), alpha = 0.2) +
geom_hline(yintercept = 0, lty = "longdash") +
geom_point() +
geom_line() +
labs(x = "Lag between NHS pathways and death data (days)",
y = "Pearson's correlation") +
large_txt
cor_vs_lag
This analysis suggests that the best lag is 15 days. We then compare and plot the number of deaths reported against the number of NHS Pathways reports lagged by 15 days.
all_tot <- all_tot %>%
rename(date_death = date) %>%
mutate(note_lag = lag(count, lag_cor$lag[l_opt]),
note_lag_c = (note_lag - mean(note_lag, na.rm = T)),
date_note = lag(date_death,16))
lag_mod <- glm(deaths ~ note_lag, data = all_tot, family = "quasipoisson")
summary(lag_mod)
##
## Call:
## glm(formula = deaths ~ note_lag, family = "quasipoisson", data = all_tot)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -19.166 -16.164 -5.141 6.484 32.725
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 5.226e+00 6.506e-02 80.334 <2e-16 ***
## note_lag 1.134e-05 1.238e-06 9.163 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for quasipoisson family taken to be 219.93)
##
## Null deviance: 81541 on 321 degrees of freedom
## Residual deviance: 67895 on 320 degrees of freedom
## (15 observations deleted due to missingness)
## AIC: NA
##
## Number of Fisher Scoring iterations: 5
exp(coefficients(lag_mod))
## (Intercept) note_lag
## 186.103914 1.000011
exp(confint(lag_mod))
## 2.5 % 97.5 %
## (Intercept) 163.449910 210.950701
## note_lag 1.000009 1.000014
Rsq(lag_mod)
## [1] 0.1673534
mod_fit <- as.data.frame(predict(lag_mod, type = "link", se.fit = TRUE)[1:2])
all_tot_pred <-
all_tot %>%
filter(!is.na(note_lag)) %>%
mutate(pred = mod_fit$fit,
pred.se = mod_fit$se.fit,
low = exp(pred - 1.96*pred.se),
hi = exp(pred + 1.96*pred.se))
glm_fit <- all_tot_pred %>%
filter(!is.na(note_lag)) %>%
ggplot(aes(x = note_lag, y = deaths)) +
geom_point() +
geom_line(aes(y = exp(pred))) +
geom_ribbon(aes(ymin = low, ymax = hi), alpha = 0.3, col = "grey") +
theme_bw() +
labs(y = "Daily number of\ndeaths reported",
x = "Daily number of NHS Pathways reports") +
large_txt
glm_fit
4 Supplementary figures
4.1 Serial interval distribution
This is a comparison of gamma versus lognormal distribution for the serial interval used to convert r to R in our analysis. Both distributions are parameterised with mean 4.7 and standard deviation 2.9.
SI_param <- epitrix::gamma_mucv2shapescale(4.7, 2.9/4.7)
SI_distribution <- distcrete::distcrete("gamma", interval = 1,
shape = SI_param$shape,
scale = SI_param$scale, w = 0.5)
SI_distribution2 <- distcrete::distcrete("lnorm", interval = 1,
meanlog = log(4.7),
sdlog = log(2.9), w = 0.5)
SI_dist1 <- data.frame(x = SI_distribution$r(1e5))
SI_dist1 <- count(SI_dist1, x) %>%
ggplot() +
geom_col(aes(x = x, y = n)) +
labs(x = "Serial interval (days)", y = "Frequency") +
scale_x_continuous(breaks = seq(0, 30, 5)) +
theme_bw()
SI_dist2 <- data.frame(x = SI_distribution2$r(1e5))
SI_dist2 <- count(SI_dist2, x) %>%
ggplot() +
geom_col(aes(x = x, y = n)) +
labs(x = "Serial interval (days)", y = "Frequency") +
scale_x_continuous(breaks = seq(0, 200, 20), limits = c(0, 200)) +
theme_bw()
ggpubr::ggarrange(SI_dist1,
SI_dist2,
nrow = 1,
labels = "AUTO") 
4.2 Sensitivity analysis - 7 or 21 days moving window
We reproduce the window analysis with either a 7 or 21 days window for sensitivity purposes.
First with the 7 days window:
## set moving time window (1/2/3 weeks)
w <- 7
# create empty df
r_all_sliding_7days <- NULL
## make data for model
x_model_all_moving <- x %>%
filter(!is.na(nhs_region)) %>%
group_by(date, nhs_region) %>%
summarise(n = sum(count))
unique_dates <- unique(x_model_all_moving$date)
for (i in 1:(length(unique_dates) - w)) {
date_i <- unique_dates[i]
date_i_max <- date_i + w
model_data <- x_model_all_moving %>%
filter(date >= date_i & date < date_i_max) %>%
mutate(day = as.integer(date - date_i)) %>%
day_of_week()
mod <- glm(n ~ day * nhs_region + day_of_week,
data = model_data,
family = 'quasipoisson')
# get growth rate
r <- get_r(mod)
r$w_min <- date_i
r$w_max <- date_i_max
# combine all estimates
r_all_sliding_7days <- bind_rows(r_all_sliding_7days, r)
}
#serial interval distribution
SI_param = epitrix::gamma_mucv2shapescale(4.7, 2.9/4.7)
SI_distribution <- distcrete::distcrete("gamma", interval = 1,
shape = SI_param$shape,
scale = SI_param$scale,
w = 0.5)
#convert growth rates r to R0
r_all_sliding_7days <- r_all_sliding_7days %>%
mutate(R = epitrix::r2R0(r, SI_distribution),
R_lower_95 = epitrix::r2R0(lower_95, SI_distribution),
R_upper_95 = epitrix::r2R0(upper_95, SI_distribution))# plot
plot_growth <-
r_all_sliding_7days %>%
ggplot(aes(x = w_max, y = r)) +
geom_ribbon(aes(ymin = lower_95, ymax = upper_95, fill = nhs_region), alpha = 0.1) +
geom_line(aes(colour = nhs_region)) +
geom_point(aes(colour = nhs_region)) +
geom_hline(yintercept = 0, linetype = "dashed") +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
plot.margin = margin(0.5,1,0.5,0.5, "cm")) +
guides(colour = guide_legend(title = "",override.aes = list(fill = NA)), fill = FALSE) +
labs(x = "",
y = "Estimated daily growth rate (r)") +
scale_colour_manual(values = pal)plot_R <- r_all_sliding_7days %>%
ggplot(aes(x = w_max, y = R)) +
geom_ribbon(aes(ymin = R_lower_95, ymax = R_upper_95, fill = nhs_region), alpha = 0.1) +
geom_line(aes(colour = nhs_region)) +
geom_point(aes(colour = nhs_region)) +
geom_hline(yintercept = 1, linetype = "dashed") +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
plot.margin = margin(0.5,1,0.5,0.5, "cm")) +
guides(color = guide_legend(title = "", override.aes = list(fill = NA)), fill = FALSE) +
labs(x = "",
y = "Estimated effective reproduction\nnumber (Re)") +
scale_colour_manual(values = pal)
R <- r_all_sliding_7days %>%
mutate(lower_95 = R_lower_95,
upper_95 = R_upper_95,
value = R,
measure = "R",
reference = 1)
r_R <- r_all_sliding_7days %>%
mutate(measure = "r",
value = r,
reference = 0) %>%
bind_rows(R)
r_R_7 <- r_R %>%
ggplot(aes(x = w_max, y = value)) +
geom_ribbon(aes(ymin = lower_95, ymax = upper_95, fill = nhs_region), alpha = 0.1) +
geom_line(aes(colour = nhs_region)) +
geom_point(aes(colour = nhs_region)) +
geom_hline(aes(yintercept = reference), linetype = "dashed") +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
plot.margin = margin(0.5,1,0,0, "cm"),
strip.background = element_blank(),
strip.placement = "outside"
) +
guides(color = guide_legend(title = "", override.aes = list(fill = NA)), fill = FALSE) +
labs(x = "", y = "") +
scale_colour_manual(values = pal) +
facet_grid(rows = vars(measure),
scales = "free_y",
switch = "y",
labeller = as_labeller(c(r = "Daily growth rate (r)",
R = "Effective reproduction\nnumber (Re)")))Then with the 21 days window:
## set moving time window (1/2/3 weeks)
w <- 21
# create empty df
r_all_sliding_21days <- NULL
## make data for model
x_model_all_moving <- x %>%
filter(!is.na(nhs_region)) %>%
group_by(date, nhs_region) %>%
summarise(n = sum(count))
unique_dates <- unique(x_model_all_moving$date)
for (i in 1:(length(unique_dates) - w)) {
date_i <- unique_dates[i]
date_i_max <- date_i + w
model_data <- x_model_all_moving %>%
filter(date >= date_i & date < date_i_max) %>%
mutate(day = as.integer(date - date_i)) %>%
day_of_week()
mod <- glm(n ~ day * nhs_region + day_of_week,
data = model_data,
family = 'quasipoisson')
# get growth rate
r <- get_r(mod)
r$w_min <- date_i
r$w_max <- date_i_max
# combine all estimates
r_all_sliding_21days <- bind_rows(r_all_sliding_21days, r)
}
#serial interval distribution
SI_param = epitrix::gamma_mucv2shapescale(4.7, 2.9/4.7)
SI_distribution <- distcrete::distcrete("gamma", interval = 1,
shape = SI_param$shape,
scale = SI_param$scale,
w = 0.5)
#convert growth rates r to R0
r_all_sliding_21days <- r_all_sliding_21days %>%
mutate(R = epitrix::r2R0(r, SI_distribution),
R_lower_95 = epitrix::r2R0(lower_95, SI_distribution),
R_upper_95 = epitrix::r2R0(upper_95, SI_distribution))# plot
plot_growth <-
r_all_sliding_21days %>%
ggplot(aes(x = w_max, y = r)) +
geom_ribbon(aes(ymin = lower_95, ymax = upper_95, fill = nhs_region), alpha = 0.1) +
geom_line(aes(colour = nhs_region)) +
geom_point(aes(colour = nhs_region)) +
geom_hline(yintercept = 0, linetype = "dashed") +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
plot.margin = margin(0.5,1,0.5,0.5, "cm")) +
guides(colour = guide_legend(title = "",override.aes = list(fill = NA)), fill = FALSE) +
labs(x = "",
y = "Estimated daily growth rate (r)") +
scale_colour_manual(values = pal)# plot
plot_R <-
r_all_sliding_21days %>%
ggplot(aes(x = w_max, y = R)) +
geom_ribbon(aes(ymin = R_lower_95, ymax = R_upper_95, fill = nhs_region), alpha = 0.1) +
geom_line(aes(colour = nhs_region)) +
geom_point(aes(colour = nhs_region)) +
geom_hline(yintercept = 1, linetype = "dashed") +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
plot.margin = margin(0.5,1,0.5,0.5, "cm")) +
guides(color = guide_legend(title = "", override.aes = list(fill = NA)), fill = FALSE) +
labs(x = "",
y = "Estimated effective reproduction\nnumber (Re)") +
scale_colour_manual(values = pal)
R <- r_all_sliding_21days %>%
mutate(lower_95 = R_lower_95,
upper_95 = R_upper_95,
value = R,
measure = "R",
reference = 1)
r_R <- r_all_sliding_21days %>%
mutate(measure = "r",
value = r,
reference = 0) %>%
bind_rows(R)
r_R_21 <- r_R %>%
ggplot(aes(x = w_max, y = value)) +
geom_ribbon(aes(ymin = lower_95, ymax = upper_95, fill = nhs_region), alpha = 0.1) +
geom_line(aes(colour = nhs_region)) +
geom_point(aes(colour = nhs_region)) +
geom_hline(aes(yintercept = reference), linetype = "dashed") +
theme_bw() +
scale_weeks +
theme(legend.position = "bottom",
plot.margin = margin(0.5,1,0,0, "cm"),
strip.background = element_blank(),
strip.placement = "outside"
) +
guides(color = guide_legend(title = "", override.aes = list(fill = NA)), fill = FALSE) +
labs(x = "", y = "") +
scale_colour_manual(values = pal) +
facet_grid(rows = vars(measure),
scales = "free_y",
switch = "y",
labeller = as_labeller(c(r = "Daily growth rate (r)",
R = "Effective reproduction\nnumber (Re)")))And we combine both outputs into a single plot:
ggpubr::ggarrange(r_R_7,
r_R_21,
nrow = 2,
labels = "AUTO",
common.legend = TRUE,
legend = "bottom") 
4.3 Correlation between NHS Pathways reports and deaths by NHS region
lag_cor_reg <- data.frame()
for (i in 0:30) {
summary <-
all_data %>%
group_by(nhs_region) %>%
mutate(note_lag = lag(count, i)) %>%
## calculate rank correlation and bootstrap CI for each region
group_modify(~getboot(.x)) %>%
mutate(lag = i)
lag_cor_reg <- bind_rows(lag_cor_reg, summary)
}
cor_vs_lag_reg <-
lag_cor_reg %>%
ggplot(aes(lag, r, col = nhs_region)) +
geom_hline(yintercept = 0, lty = "longdash") +
geom_ribbon(aes(ymin = r_low, ymax = r_hi, col = NULL, fill = nhs_region), alpha = 0.2) +
geom_point() +
geom_line() +
facet_wrap(~nhs_region) +
scale_color_manual(values = pal) +
scale_fill_manual(values = pal, guide = F) +
theme_bw() +
labs(x = "Lag between NHS pathways and death data (days)", y = "Pearson's correlation", col = "NHS region") +
theme(legend.position = "bottom") +
guides(color = guide_legend(override.aes = list(fill = NA)))
cor_vs_lag_reg
5 Export data
We save the tables created during our analysis:
if (!dir.exists("excel_tables")) {
dir.create("excel_tables")
}
## list all tables, and loop over export
tables_to_export <- c("r_all_sliding", "lag_cor")
for (e in tables_to_export) {
rio::export(get(e),
file.path("excel_tables",
paste0(e, ".xlsx")))
}
## also export result from regression on lagged data
rio::export(lag_mod, file.path("excel_tables", "lag_mod.rds"))6 System information
6.1 Outline
The following information documents the system on which the document was compiled.
6.2 System
This provides information on the operating system.
Sys.info()
## sysname
## "Darwin"
## release
## "19.6.0"
## version
## "Darwin Kernel Version 19.6.0: Tue Jan 12 22:13:05 PST 2021; root:xnu-6153.141.16~1/RELEASE_X86_64"
## nodename
## "Mac-1615543790333.local"
## machine
## "x86_64"
## login
## "root"
## user
## "runner"
## effective_user
## "runner"6.3 R environment
This provides information on the version of R used:
6.4 R packages
This provides information on the packages used:
sessionInfo()
## R version 4.0.4 (2021-02-15)
## Platform: x86_64-apple-darwin17.0 (64-bit)
## Running under: macOS Catalina 10.15.7
##
## Matrix products: default
## BLAS: /Library/Frameworks/R.framework/Versions/4.0/Resources/lib/libRblas.dylib
## LAPACK: /Library/Frameworks/R.framework/Versions/4.0/Resources/lib/libRlapack.dylib
##
## locale:
## [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
##
## attached base packages:
## [1] stats graphics grDevices utils datasets methods base
##
## other attached packages:
## [1] ggnewscale_0.4.5 ggpubr_0.4.0 lubridate_1.7.10
## [4] chngpt_2020.10-12 cyphr_1.1.0 DT_0.17
## [7] kableExtra_1.3.4 janitor_2.1.0 remotes_2.2.0
## [10] projections_0.5.2 earlyR_0.0.5 epitrix_0.2.2
## [13] distcrete_1.0.3 incidence_1.7.3 rio_0.5.26
## [16] reshape2_1.4.4 rvest_1.0.0 xml2_1.3.2
## [19] linelist_0.0.40.9000 forcats_0.5.1 stringr_1.4.0
## [22] dplyr_1.0.5 purrr_0.3.4 readr_1.4.0
## [25] tidyr_1.1.3 tibble_3.1.0 ggplot2_3.3.3
## [28] tidyverse_1.3.0 here_1.0.1 reportfactory_0.0.5
##
## loaded via a namespace (and not attached):
## [1] minqa_1.2.4 colorspace_2.0-0 selectr_0.4-2 ggsignif_0.6.1
## [5] ellipsis_0.3.1 rprojroot_2.0.2 snakecase_0.11.0 fs_1.5.0
## [9] rstudioapi_0.13 farver_2.1.0 fansi_0.4.2 splines_4.0.4
## [13] knitr_1.31 jsonlite_1.7.2 nloptr_1.2.2.2 broom_0.7.5
## [17] dbplyr_2.1.0 compiler_4.0.4 httr_1.4.2 backports_1.2.1
## [21] assertthat_0.2.1 Matrix_1.3-2 cli_2.3.1 htmltools_0.5.1.1
## [25] tools_4.0.4 gtable_0.3.0 glue_1.4.2 Rcpp_1.0.6
## [29] carData_3.0-4 cellranger_1.1.0 vctrs_0.3.6 svglite_2.0.0
## [33] nlme_3.1-152 matchmaker_0.1.1 crosstalk_1.1.1 xfun_0.22
## [37] ps_1.6.0 openxlsx_4.2.3 lme4_1.1-26 lifecycle_1.0.0
## [41] statmod_1.4.35 rstatix_0.7.0 MASS_7.3-53 scales_1.1.1
## [45] hms_1.0.0 parallel_4.0.4 sodium_1.1 yaml_2.2.1
## [49] curl_4.3 gridExtra_2.3 stringi_1.5.3 highr_0.8
## [53] kyotil_2020.10-12 boot_1.3-26 zip_2.1.1 rlang_0.4.10
## [57] pkgconfig_2.0.3 systemfonts_1.0.1 evaluate_0.14 lattice_0.20-41
## [61] labeling_0.4.2 htmlwidgets_1.5.3 cowplot_1.1.1 tidyselect_1.1.0
## [65] plyr_1.8.6 magrittr_2.0.1 R6_2.5.0 generics_0.1.0
## [69] DBI_1.1.1 mgcv_1.8-33 pillar_1.5.1 haven_2.3.1
## [73] foreign_0.8-81 withr_2.4.1 survival_3.2-7 abind_1.4-5
## [77] modelr_0.1.8 crayon_1.4.1 car_3.0-10 utf8_1.1.4
## [81] rmarkdown_2.7 viridis_0.5.1 grid_4.0.4 readxl_1.3.1
## [85] data.table_1.14.0 reprex_1.0.0 digest_0.6.27 webshot_0.5.2
## [89] munsell_0.5.0 viridisLite_0.3.0